Detecting sepsis

ABSTRACT

A method for predicting sepsis or diagnosing systemic inflammatory response syndrome (SIRS) and/or sepsis in a subject comprises determining levels of at least three markers selected from CCL23, A1AT, CRP, sICAM, PLA2, IL-6, procalcitonin, MMP8, TNFalpha, AcPGP, enzymatic MMP activity, TIMP1, sRAGE and desmosine in a sample taken from the subject. The combined levels of the at least three markers are used to predict or diagnose SIRS and/or sepsis. The methods may be performed on a subject with SIRS and which is used to identify an infection in the subject. A preferred panel of markers includes CCL23, A1AT, sICAM, sICAM/VCAM-1 and CRP. Corresponding products, methods of treatment and medical uses are provided.

CROSS REFERENCE TO RELATED APPLICATION

The present application is the U.S. national stage of InternationalApplication PCT/GB2017/050847, filed on Mar. 24, 2017, whichinternational application was published on Sep. 28, 2017 asInternational Publication No. WO2017/163087. The InternationalApplication claims priority to British Patent Application No. GB1605110.4, filed on Mar. 24, 2016, the contents of which areincorporated herein by reference in their entireties.

FIELD OF THE INVENTION

The present invention relates to the identification of markers thatpredict or diagnose systemic inflammatory response syndrome (SIRS) andsepsis. In particular, the invention relates to monitoring subjectssubjected to a surgical procedure for SIRS and sepsis based uponmeasuring markers at multiple time points.

BACKGROUND TO THE INVENTION

Sepsis is a major and increasing public health concern. The clinicalpresentation of sepsis is such that it is difficult to diagnose and, inparticular, to distinguish from Systemic Inflammatory Response Syndrome(SIRS). A number of diagnostic tools (i.e. lactate, blood culture, WBCcounts, CRP etc.) are available to assist in the identification ofsepsis but these lack sensitivity and/or specificity. The pressures toinitiate treatment of sepsis as early as possible (because mortalityrisk increases for every hour of delay before initiation of therapy) canlead to the inappropriate use of broad spectrum antibiotics beforeconfirmation of diagnosis, which can take up to 72 hours. Rapid decisionmaking is critical to the appropriate treatment of the patient and thereduction of morbidity and mortality. Incorrect prescription ofantibiotics fuels antibiotic resistance and in many cases causes severeadverse drug reactions.

DESCRIPTION OF THE INVENTION

There is a need for a more sensitive and specific assay for sepsis thatcould be deployed in near patient settings or at the point of care. Thepresent inventors have identified combinations of markers that areeffective in predicting and diagnosing SIRS and sepsis.

Accordingly, in a first aspect, the invention provides a method forpredicting or diagnosing systemic inflammatory response syndrome (SIRS)and/or sepsis in a subject, the method comprising determining levels ofat least one, two or three markers selected from PLA2 (phospholipaseA2), CRP (C-reactive protein), CCL23 (chemokine (C—C motif) ligand 23),sICAM (soluble Intercellular Adhesion Molecule 1), IL-6 (interleukin-6),procalcitonin, A1AT (alpha-1 antitrypsin), MMP8 (MatrixMetalloproteinase-8), TNFalpha (Tumour Necrosis Factor alpha), AcPGP(N-acetyl Proline-Glycine-Proline), enzymatic MMP activity, TIMP1(Tissue Inhibitor of Metalloproteinase 1), sRAGE (soluble form ofReceptor for Advanced Glycated End-products) and desmosine in a sampletaken from the subject, wherein the (combined) levels of the at leastone, two or three markers are used to predict or diagnose SIRS and/orsepsis.

It should be noted that throughout the specification the term“comprising” is intended to represent open-ended (i.e. including)language. However, for the avoidance of doubt, wherever the term“comprising” is used it is envisaged that the corresponding feature maybe limited to that specified (i.e. consisting) as necessary.

The methods may be applied to patients who are potentially at high riskof developing sepsis. They may for example be applied to routinely testpatients admitted to hospital, or to patients in the intensive careunit. The patients may be immunocompromised patients.

The methods may be repeated at regular intervals in relation to the samepatient, in particular to monitor and predict sepsis (including itsdevelopment from SIRS).

SIRS is an inflammatory state affecting the whole body. The four SIRScriteria are (Bone et al. Crit Care Med. 1992; 20(6)864-874):

-   -   1. Temperature >38° C. or <36° C.    -   2. Heart rate >90/min    -   3. Respiratory rate >20/min or PaCO₂<32 mm Hg (4.3 kPa)    -   4. White blood cell count >12000/mm³ or <4000/mm³ or >10%        immature bands

When two or more of these criteria are met patients may be diagnosedwith SIRS.

Sepsis presents as a syndrome with physiological, pathological andbiochemical abnormalities caused by infection. As with many conditionsthe definition of sepsis has been updated over time. Sepsis may bedefined as infection with at least 2 SIRS criteria. Sepsis may also bedefined as SIRS in the presence of a confirmed or suspected infection.

A new definition of sepsis as a life-threatening organ dysfunctioncaused by a dysregulated host response to infection has been proposed(Singer et al. JAMA 2016; 315(8):801-810). The present invention isconsidered to be equally applicable to the evolving definitions ofsepsis. The present invention is also applicable to identifyinginfection in a SIRS patient, irrespective of sepsis-related organdysfunction assessment (SOFA) score. Thus, sepsis may be distinguishedfrom SIRS.

SIRS and sepsis are commonly developed after surgery. The presentinventors have shown that the markers described herein can be used forthe surveillance of patients undergoing surgery. The combinations ofmarkers described herein have been shown by the inventors to predictsepsis and to allow sepsis and SIRS to be distinguished. This willenable improved management of surgical patients resulting in improvedpatient outcomes and substantial health-economic benefits.

Thus, the invention provides a method for monitoring a subject at riskof developing sepsis, the method comprising determining levels of atleast one, at least two or at least three markers in samples taken fromthe subject at multiple time points, wherein the monitored levels of theat least one, at least two or at least three markers are used to predictor diagnose SIRS and/or sepsis.

More specifically, the invention also provides a method for monitoring asubject subjected to a surgical procedure, the method comprisingdetermining levels of at least one, at least two or at least threemarkers in samples taken from the subject at multiple time pointsincluding a first sample taken from the subject prior to the surgery toprovide baseline levels of the markers and at least one further sampletaken from the subject following surgery, wherein the monitored levelsof the at least one, at least two or at least three markers are used topredict or diagnose SIRS and/or sepsis following surgery.

In certain embodiments the methods of the invention discriminate SIRSfrom sepsis. The method may provide a prediction of impending sepsis.For example, the method may predict impending sepsis 1, 2, or 3 daysbefore sepsis develops or would develop in the absence of treatment. Theprediction of impending sepsis may result in treatment of the infection.In certain embodiments, the subject is not treated (e.g. with anantibiotic) unless and until impending sepsis is predicted or sepsis isdiagnosed (according to the methods of the invention). In this wayunnecessary treatment is avoided.

In certain embodiments according to all aspects of the invention the atleast one, at least two or at least three markers are selected fromPLA2, CRP, CCL23, sICAM, IL-6, procalcitonin, A1AT, MMP8, TNFalpha,AcPGP, enzymatic MMP activity, TIMP1, sRAGE and desmosine. The PLA2 maybe of group IIA i.e. PLA2G2A.

In some embodiments, the methods of the invention are performed on asubject with SIRS. In such embodiments, the methods may be used toidentify an infection in the subject. Suitable markers for use in suchmethods may be selected from 1, 2, 3, 4, 5, 6, 7, 8, 9 or all ofdesmosine, TNF, IL-6, AcPGP, PLA2g2A, CCL23, A1AT, sICAM (optionallymeasured by ELISA), sICAM/VCAM-1 (optionally measured by lateral flow)and CRP. More specifically, the markers may be selected from one, two,three, four of all of CCL23, A1AT, sICAM (optionally measured by ELISA),sICAM/VCAM-1 (optionally measured by lateral flow) and CRP. Theinventors have discovered that their lateral flow format for detectingsICAM1, described in further detail herein, relies on antibody bindingto tandem N-terminal Ig-like domains (D1 and D2) of sICAM (CD54) andVCAM-1 (CD106) markers. sICAM specific measurements are also possible,using different antibodies (e.g. the ELISA formats discussed in greaterdetail herein). Thus, the methods of the invention may detect both sICAMindividually and a combination of sICAM and VCAM-1. The combination isreferred to herein as a single marker “sICAM/VCAM-1”. Both measurementshave been shown to give diagnostically useful information. Where “sICAM”is mentioned without further reference to “sICAM/VCAM-1” it is intendedthat either sICAM alone and/or sICAM/VCAM-1 may be measured.

For general monitoring, at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13or 14 or more samples may be taken from the subject at different timesand the levels of the at least three markers is determined. The samplesmay be taken every 1, 2, 3, 4, 5, 6 days or weekly for example. Thisdepends on the nature of the subject and the perceived risk of sepsis.For example, samples may be taken more frequently, such as daily forpatients in intensive case. They may be taken less frequently forimmunocompromised patients, where the risks associated with taking ablood sample have to be balanced. The frequency of sampling may varydepending on the results of the previous test. Thus, more frequenttesting may be undertaken where altered levels of the multiple markersare detected but that do not yet predict or diagnosis sepsis and/orSIRS. Conversely, detection of stable levels in multiple samples maylead to a reduction in frequency of testing, or cessation.

In relation to post-surgical monitoring, at least 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13 or 14 or more samples are taken from the subject atdifferent times after surgery and the levels of the at least threemarkers is determined. The samples may be taken every 1, 2, 3, 4, 5, 6,12 or 24 hours. For example, samples may be taken daily. The frequencyof sampling may vary depending on the time post-surgery. For example,for the first 24 hours following surgery samples may be taken hourly.After the first 24 hours the frequency of sampling may decrease, forexample to every 6, 12 or 24 hours, particularly where no indication ofsepsis has been detected in the first 24 hours. Sampling may continuefor 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14 days followingsurgery. After 14 days the occurrence of sepsis or SIRS as a result ofsurgery is very low.

The methods of the invention may be implemented in a composition ofmatter which may take the form of a system or test kit. Such a system ortest kit is preferably suitable for use, and ideally very easy to use(e.g. with a readily interpreted output), by clinicians in a healthcaresetting such as a hospital.

Accordingly, the invention also provides a system or test kit forpredicting or diagnosing systemic inflammatory response syndrome (SIRS)and/or sepsis in a subject, comprising:

-   -   a. One or more testing devices for determining levels of at        least one, two or three markers selected from PLA2, CRP, CCL23,        sICAM, IL-6, procalcitonin, A1AT, MMP8, TNFalpha, AcPGP,        enzymatic MMP activity, TIMP1, sRAGE and desmosine in a sample    -   b. A processor; and    -   c. A storage medium comprising a computer application that, when        executed by the processor, is configured to:        -   i. Access and/or calculate the determined levels of each            marker in the sample on the one or more testing devices        -   ii. Calculate a test score from the levels of the markers in            the sample that predicts or diagnoses SIRS and/or sepsis;            and        -   iii. Output from the processor the predicted or diagnostic            result for the subject.

Also provided is a system or test kit for monitoring a subject,comprising:

-   -   a. One or more testing devices for determining levels of at        least one, two or three markers selected from PLA2, CRP, CCL23,        sICAM, IL-6, procalcitonin, A1AT, MMP8, TNFalpha, AcPGP,        enzymatic MMP activity, TIMP1, sRAGE and desmosine TNFalpha in a        sample at multiple time points    -   b. A processor; and    -   c. A storage medium comprising a computer application that, when        executed by the processor, is configured to:        -   i. Access and/or calculate the determined levels of each            marker in the sample on the one or more testing devices        -   ii. Calculate a test score from the levels of the markers in            the sample, optionally including a comparison of the levels            with those taken at one or more earlier time points, to            thereby predict or diagnose SIRS and/or sepsis; and        -   iii. Output from the processor the predicted or diagnostic            result for the subject.

Also provided is a system or test kit for monitoring a subject subjectedto a surgical procedure, comprising:

-   -   a. One or more testing devices for determining levels of at        least one, two or three markers selected from PLA2, CRP, CCL23,        sICAM, IL-6, procalcitonin, A1AT, MMP8, TNFalpha, AcPGP,        enzymatic MMP activity, TIMP1, sRAGE and desmosine in a sample        at multiple time points including a first sample taken from the        subject prior to the surgery to provide baseline levels of the        markers and at least one further sample taken from the subject        following surgery    -   b. A processor; and    -   c. A storage medium comprising a computer application that, when        executed by the processor, is configured to:        -   i. Access and/or calculate the determined levels of each            marker in the sample on the one or more testing devices        -   ii. Calculate a test score from the levels of the markers in            the sample by comparing the levels with those taken at one            or more earlier time points to thereby predict or diagnose            SIRS and/or sepsis; and        -   iii. Output from the processor the predicted or diagnostic            result for the subject.

The invention also relates to a corresponding computer application foruse in the system or test kit.

The invention provides for patient selection for therapy and, thus,avoids unnecessary treatment with antibiotics. Incorrect use ofantibiotics fuels antibiotic resistance and can cause severe adversedrug reactions.

Accordingly, the invention also relates to a method of selecting asubject for treatment with an antibiotic comprising performing a methoddescribed herein and selecting the subject for treatment where sepsis ispredicted or diagnosed.

In a related aspect, the present invention provides a method ofpredicting responsiveness of a subject to treatment with an antibioticcomprising performing a method described herein and predictingresponsiveness of the subject to treatment where sepsis is predicted ordiagnosed.

In a further aspect the invention provides a method of treating sepsiscomprising administering an antibiotic to the subject suffering fromsepsis, wherein the subject has been selected for treatment byperforming a method described herein.

The invention also relates to a method of treating sepsis comprisingadministering an antibiotic to the subject suffering from sepsis,wherein the subject displays, in a sample, an altered level of at leastone, two or three markers selected from PLA2, CRP, CCL23, sICAM, IL-6,procalcitonin, A1AT, MMP8, TNFalpha, AcPGP, enzymatic MMP activity,TIMP1, sRAGE and desmosine.

In yet a further aspect, the present invention provides an antibioticfor use in a method of treating sepsis, wherein the subject has beenselected for treatment by performing the method described herein.

According to a further aspect of the invention there is provided anantibiotic for use in a method of treating sepsis, wherein the subjectdisplays, in a sample, an altered level of at least one, two or threemarkers selected from PLA2, CRP, CCL23, sICAM, IL-6, procalcitonin,A1AT, MMP8, TNFalpha, AcPGP, enzymatic MMP activity, TIMP1, sRAGE anddesmosine.

In certain embodiments the antibiotic is a broad spectrum antibiotic.This is particularly useful if sepsis is diagnosed but where the originof the infection has not yet been characterised. Once sepsis has beendiagnosed, the infection may be characterised so as to allow moretargeted therapy (e.g. as bacterial, which may be gram-positive orgram-negative), or fungal. The antibiotic may be selected from anaminoglycoside, a cephalosporin, a glycopeptide, a penicillin, aquinolone, aztreonam, clindamycin, imipenem-cilastin, linezolid,metronidazole, rifampin and an antifungal. Thus, combinations of broadspectrum antibiotics and more focussed therapies may be employed as partof the methods described herein.

The invention also provides a testing device, testing kit or testingcomposition of matter comprising:

-   -   a. A sample receiving zone to which a sample from a subject is        added    -   b. A conjugate zone comprising at least one, two or three        labelled binding reagents, each of which specifically binds to        one of the at least one, two or three markers selected from        PLA2, CRP, CCL23, sICAM, IL-6, procalcitonin, A1AT, MMP8,        TNFalpha, AcPGP, enzymatic MMP activity, TIMP1, sRAGE and        desmosine    -   c. A solid support defining a liquid flow path for the sample        and comprising corresponding test lines for each of the at least        three markers, each test line comprising an immobilised further        binding reagent that also specifically binds to one of the at        least three markers thereby immobilising the marker at the test        line to produce a signal via the labelled binding reagent also        specifically bound to the marker.

The testing device, testing kit or testing composition of matter mayfurther comprise:

-   -   d. At least one labelled control binding reagent that binds to a        binding partner immobilised at a control line downstream of the        test lines for the at least one, two or three markers and thus        confirms that the test has completed successfully.

The testing device, testing kit or testing composition of matter mayfurther comprise:

-   -   e. An absorbent material downstream of the test (and control,        where present) lines to absorb excess sample.

In specific embodiments the sample receiving zone is proportioned toreceive between 10 and 100 μl of serum, such as around 80 μl of serum

In specific embodiments, the solid support comprises a chromatographicmedium or a capillary flow device. The invention may be provided in atest strip format in some embodiments.

The testing device, testing kit or testing composition of matter mayfurther comprise a reader to quantify levels of the markers at therespective test lines. The reader may further comprise:

-   -   a. A processor; and    -   b. A storage medium comprising a computer application that, when        executed by the processor, is configured to:        -   i. Access and/or calculate the determined levels of each            marker in the sample on the one or more testing devices        -   ii. Calculate a test score from the levels of the markers in            the sample that predicts or diagnoses SIRS and/or sepsis;            and        -   iii. Output from the processor the predicted or diagnostic            result for the subject.

In other embodiments the reader further comprises:

-   -   a. A processor; and    -   d. A storage medium comprising a computer application that, when        executed by the processor, is configured to:        -   i. Access and/or calculate the determined levels of each            marker in the sample on the one or more testing devices        -   ii. Calculate a test score from the levels of the markers in            the sample by comparing the levels with those taken at one            or more earlier time points to thereby predict or diagnose            SIRS and/or sepsis; and        -   iii. Output from the processor the predicted or diagnostic            result for the subject.

According to all aspects of the invention the levels of at least 4, 5,6, 7, 8, 9, 10, 11, 12, 13 or more markers may be determined.

As discussed above, markers of the invention may be measured in samplesfrom a subject with SIRS. In such embodiments, the markers may be usedto identify an infection in the subject. Suitable markers may beselected from 1, 2, 3, 4, 5, 6, 7, 8, 9 or all of desmosine, TNF, IL-6,AcPGP, PLA2g2A, CCL23, A1AT, sICAM (optionally measured by ELISA),sICAM/VCAM-1 (optionally measured by lateral flow) and CRP. Morespecifically, the markers may be selected from one, two, three, four ofall of CCL23, A1AT, sICAM (optionally measured by ELISA), sICAM/VCAM-1(optionally measured by lateral flow) and CRP. The markers may includeboth sICAM individually and a combination of sICAM and VCAM-1. Thecombination is referred to herein as a single marker “sICAM/VCAM-1”.Both measurements have been shown to give diagnostically usefulinformation. Where “sICAM” is mentioned without further reference to“sICAM/VCAM-1” it is intended that either sICAM alone and/orsICAM/VCAM-1 may be measured.

Markers that have been shown to be particularly useful individually inpredicting or diagnosing sepsis include CRP, PLA2 and sICAM. Thus,according to all aspects of the invention at least one of the markersmay be selected from CRP, PLA2 and sICAM. In some embodiments, the atleast three markers are selected from sICAM, CCL23, A1AT, CRP, IL-6,PLA2G2A and TNFalpha.

Specific marker combinations which may be useful in the inventioninclude CRP, sICAM and TNFalpha. In certain embodiments the levels of atleast four markers are determined. Thus, a further specific markercombination which may be useful in the invention is PLA2, IL-6, CRP andTNFalpha. A further specific marker combination which may be useful inthe invention is sICAM, CCL23, A1AT, CRP, IL-6 and TNFalpha. A stillfurther marker combination shown to be useful in the invention comprisesor is CRP, sICAM and IL-6. In certain embodiments sICAM is measured byan ELISA and a lateral flow assay (i.e. both sICAM and sICAM/VCAM-1 maybe measured).

The markers may comprise one or more, up to all, of IL-6, TIMP1, sICAM-1and PLA2. IL-6, TIMP1, sICAM-1 and PLA2 are early markers of sepsis.They may be more useful than CRP in early detection or prediction ofsepsis as shown herein. Accordingly, these markers will usefully bemeasured rapidly following an indication that a subject may have sepsis,for example in testing high risk patients such as immunocompromisedpatients and those in intensive care and/or following surgery. Forexample, these markers may be measured within 6 hours of an indicationof sepsis or following surgery. In certain embodiments these markers aremeasured every 1, 2, 3, 4, 5 or 6 hours for up to 14 days following theindication of sepsis or the surgery.

By “altered” levels is meant an increase or decrease compared tothreshold levels. Threshold levels may be defined from populationstudies or be specific to the individual. Where specific to theindividual, the levels may reflect those taken at an earlier time point.In some embodiments, that earlier time point is prior to surgery.Threshold levels may be set with reference to a training data setcomprising samples defined in relation to sepsis and/or SIRS status.Because the threshold levels vary according to the measuring techniqueadopted they are not stated as fixed values but can be implementedaccording to the present invention by one skilled in the art. Examplethresholds are set forth herein for information purposes.

According to the invention, the following markers are typicallyincreased in level to predict or diagnose sepsis: PLA2, CRP, CCL23,sICAM, IL-6, procalcitonin, A1AT, MMP8, TNFalpha, a substrate ofenzymatic MMP activity, TIMP1, desmosine and sRAGE.

According to the invention, AcPGP may be decreased in level to predictor diagnose sepsis.

The subject is a mammalian subject, typically a human.

It should be noted that the invention is performed in vitro based uponisolated whole blood, plasma or serum samples. The methods of theinvention therefore typically do not (although they may) include stepsof obtaining a sample for testing in some embodiments. However, thesample may be obtained simply, for example by finger prick. This isparticularly advantageous from a compliance perspective and providesadequate volume for the various testing devices described herein, inparticular the lateral flow formats in which multiple markers aredetermined from a single sample. Similarly, in some embodiments, thesystems and test kits include suitable vessels for receiving a sample.The container may be coloured to protect any light sensitive analytes.

There are various known techniques by which marker levels may bemeasured. Thus, by marker levels is meant the level of expression and/oractivity and/or amount and/or concentration of the marker. Expressionlevels of the markers may be measured in blood. Expression levels maycorrelate with activity and can thus be used as a surrogate of activity.Expression levels may be measured at the level of protein or mRNAaccording to any suitable method. Protein modifications, such asglycosylation may also be relevant and can be measured by any suitablemethod. Many such methods are well known in the art and include use ofmass spectrometry (e.g. MALDI-TOF mass spectrometry). MicroRNAs may alsobe measured in samples as post-transcriptional regulators of geneexpression. A platform such as that offered by Exiqon may be utilised toprovide high-throughput microRNA profiling. Such platforms may be arrayand/or PCR based.

The expression level and/or amount and/or concentration of a marker(e.g. a protein) may rely upon a binding reagent such as an antibody oraptamer that binds specifically to the marker of interest (e.g.protein). The antibody may be of monoclonal or polyclonal origin.Fragments and derivative antibodies may also be utilised, to includewithout limitation Fab fragments, ScFv, single domain antibodies,nanoantibodies, heavy chain antibodies, aptamers etc. which retainspecific binding function and these are included in the definition of“antibody”. Such antibodies are useful in the methods of the invention.They may be used to measure the level of a particular marker (e.g.protein, or in some instances one or more specific isoforms of aprotein. The skilled person is well able to identify epitopes thatpermit specific isoforms to be discriminated from one another).

Methods for generating specific antibodies are known to those skilled inthe art. Antibodies may be of human or non-human origin (e.g. rodent,such as rat or mouse) and be humanized etc. according to knowntechniques (Jones et al., Nature (1986) May 29-Jun. 4; 321(6069):522-5;Roguska et al., Protein Engineering, 1996, 9(10):895-904; and Studnickaet al., Humanizing Mouse Antibody Frameworks While Preserving 3-DStructure. Protein Engineering, 1994, Vol. 7, pg 805).

In certain embodiments the expression level and/or amount and/orconcentration of a marker is determined using an antibody or aptamerconjugated to a label. By label is meant a component that permitsdetection, directly or indirectly. For example, the label may be anenzyme, optionally a peroxidase, or a fluorophore. Gold labels may beutilised, e.g. in the form of colloidal gold.

A label is an example of a detection agent. By detection agent is meantan agent that may be used to assist in the detection of theantibody-marker (e.g. protein) complex. Where the antibody is conjugatedto an enzyme the detection agent may comprise a chemical compositionsuch that the enzyme catalyses a chemical reaction to produce adetectable product. The products of reactions catalysed by appropriateenzymes can be, without limitation, fluorescent, luminescent, orradioactive or they may absorb or reflect visible or ultraviolet light.Examples of detectors suitable for detecting such detectable labelsinclude, without limitation, x-ray film, radioactivity counters,scintillation counters, spectrophotometers, colorimeters, fluorometers,luminometers, photodetectors and densitometers. In certain embodimentsthe detection agent may comprise a secondary antibody. The expressionlevel is then determined using an unlabelled primary antibody that bindsto the target protein and a secondary antibody conjugated to a label,wherein the secondary antibody binds to the primary antibody.

Additional techniques for determining expression level at the level ofprotein and/or the amount and/or concentration of a marker include, forexample, Western blot, immunoprecipitation, immunocytochemistry, massspectrometry, ELISA and others (see ImmunoAssay: A Practical Guide,edited by Brian Law, published by Taylor & Francis, Ltd., 2005 edition).To improve specificity and sensitivity of an assay method based onimmunoreactivity, monoclonal antibodies are often used because of theirspecific epitope recognition. Polyclonal antibodies have also beensuccessfully used in various immunoassays because of their increasedaffinity for the target as compared to monoclonal antibodies. Levels ofprotein may be detected using a lateral flow assay in some embodiments(discussed in further detail herein).

Measuring mRNA in a biological sample may be used as a surrogate fordetection of the level of the corresponding protein in the urine sample.Thus, the expression level of any of the relevant markers describedherein can also be detected by detecting the appropriate RNA.

Accordingly, in specific embodiments the expression level is determinedby microarray, northern blotting, or nucleic acid amplification. Nucleicacid amplification includes PCR and all variants thereof such asreal-time and end point methods and qPCR. Other nucleic acidamplification techniques are well known in the art, and include methodssuch as NASBA, 3SR and Transcription Mediated Amplification (TMA). Othersuitable amplification methods include the ligase chain reaction (LCR),selective amplification of target polynucleotide sequences (U.S. Pat.No. 6,410,276), consensus sequence primed polymerase chain reaction(U.S. Pat. No. 4,437,975), arbitrarily primed polymerase chain reaction(WO 90/06995), invader technology, strand displacement technology,recombinase polymerase amplification (RPA), nicking enzyme amplificationreaction (NEAR) and nick displacement amplification (WO 2004/067726).This list is not intended to be exhaustive; any nucleic acidamplification technique may be used provided the appropriate nucleicacid product is specifically amplified. Design of suitable primersand/or probes is within the capability of one skilled in the art.Various primer design tools are freely available to assist in thisprocess such as the NCBI Primer-BLAST tool. Primers and/or probes may beat least 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 or 25 (or more)nucleotides in length. mRNA expression levels may be measured by reversetranscription quantitative polymerase chain reaction (RT-PCR followedwith qPCR). RT-PCR is used to create a cDNA from the mRNA. The cDNA maybe used in a qPCR assay to produce fluorescence as the DNA amplificationprocess progresses. By comparison to a standard curve, qPCR can producean absolute measurement such as number of copies of mRNA per cell.Northern blots, microarrays, Invader assays, and RT-PCR combined withcapillary electrophoresis have all been used to measure expressionlevels of mRNA in a sample. See Gene Expression Profiling: Methods andProtocols, Richard A. Shimkets, editor, Humana Press, 2004.

RNA expression may be determined by hybridization of RNA to a set ofprobes. The probes may be arranged in an array. Microarray platformsinclude those manufactured by companies such as Affymetrix, Illumina andAgilent. RNA expression may also be measured using next generationsequencing methods, such as RNA-seq. This may require conversion of RNAto cDNA or may be a direct RNA sequencing methodology.

Similarly, activity, such as enzymatic activity, may be measured in thesample. Enzymatic activity may be measured for example by detectingprocessing of a substrate, which may be labelled, in the sample. Forexample, the assay may be a fluorogenic substrate assay. Enzyme activitymay be detected using a suitable lateral flow assay. Examples ofsuitable assay formats include the assays set forth in InternationalPatent Applications WO2009/024805, WO2009/063208, WO2007/128980,WO2007/096642, WO2007/096637, WO2013/156794 and WO2013/156795 (thecontent of each of which is hereby incorporated by reference).

Some examples of suitable assay formats useful for particular markersare outlined in the table below:

Marker Assay Type Format Supplier CRP ELISA Sandwich R&D Systems CRPLateral flow Sandwich Mologic sICAM1 ELISA Sandwich R&D Systems sICAM1Lateral flow Sandwich Mologic CRP/sICAM1 Duplex Lateral flow SandwichMologic IL-6 ELISA Sandwich R&D Systems IL-6 Lateral flow SandwichMologic PLA2 ELISA Sandwich Mologic PLA2 Lateral flow Sandwich MologicIL-6/PLA2 Duplex Lateral flow Sandwich Mologic A1AT ELISA SandwichMologic A1AT Lateral flow Sandwich Mologic TNFα ELISA Sandwich R&DSystems TNFα Lateral flow Sandwich Mologic CCL23 ELISA Sandwich R&DSystems Ac-PGPv3 ELISA Competition Mologic MMP activity SubstrateFluorescent Mologic Creatinine Substrate Colourmetric R&D SystemsDesmosine ELISA Competition Mologic MMP8 ELISA Sandwich R&D SystemsProcalcitonin ELISA Sandwich Abcam Procalcitonin ELISA Sandwich Mologic

Thus, it can be readily seen that ELISA and lateral flow formats areparticularly applicable to the present invention. In some embodiments,double antibody sandwich immunoassay (DASIA), also called sandwichELISA, or immunometric assay formats may be employed.

The inventors have devised various assays for determining the levels ofthe markers described herein.

One marker useful in the present invention is CCL23, a chemokinesecreted by a variety of cell types, including monocytes, macrophages,and dendritic cells. It has been shown to be induced by the chemokinesIL-4 and IL-13. According to the invention CCL23 may be detected by animmunoassay such as an ELISA (enzyme-linked immunosorbent assay). Theinvention thus provides an ELISA for detecting CCL23 in a samplecomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human CCL23) that specifically binds to CCL23 in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being goat polyclonal CCL23        antibody) that specifically binds to CCL23 to the sample, which        reagent is conjugated to a label (such as biotin)    -   (c) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin)    -   (d) removing reagent not bound to the immunocapture surface    -   (e) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of CCL23 in the sample.

More specifically, the invention provides an ELISA for detecting CCL23in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human CCL23, catalogue number 841474 R&D systems) that        specifically binds to CCL23 in the sample (for a defined time        such as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as R&D diluent, catalogue number DY995        R&D systems) for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 10 in sample diluent PBS,        pH6.9, supplemented with 1% BSA incubated for a defined time        such as 2 hours    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being goat polyclonal CCL23        antibody catalogue number 841475 R&D systems) that specifically        binds to CCL23 in the sample, which reagent is conjugated to a        label (such as biotin) for a defined time such as 2 hours    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin,        catalogue number 890803 R&D systems) for a defined time such as        20 minutes    -   (j) Adding a substrate that initiates the colour change (such as        OPD, catalogue number P9187 Sigma-Aldrich)    -   (k) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of CCL23 in the sample        with a specified sensitivity (such as 15.6 pg/mL) and an assay        range (such as 0.156-10 ng/mL)

A schematic representation of a suitable assay format is shown in FIG.15A and a representative calibration curve for this assay is shown inFIG. 15B.

CCL23 may be detected in a lateral flow format in other embodiments. Asuitable assay may comprise steps of:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being mouse anti-CCL23 Fab 01041-BSA        conjugated immobilised at a concentration of 1 mg/mL) that        specifically binds to CCL23 in the sample    -   (b) addition of sample diluted 1 in 2 in sample diluent PBS,        pH6.9, supplemented with 1% (v/v) Tween 20+1% BSA    -   (c) CCL23 in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being mouse anti-CCL23 Fab 01341 BSA conjugated        antibody), which reagent is conjugated to a label (such as a        gold particle, optionally a 40 nm gold particle at 15 μg/mL in        TES, pH7.5 buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of CCL23 in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete.

A suitable assay format is shown schematically in FIG. 16.

Another marker useful in the present invention is CRP (C-reactiveprotein). CRP levels increase in patients with infection beyond levelsfound in non-sepsis patients with similar organ dysfunction (Castelli,Pognani, Meisner, Stuami, Bellomi, & Sgarbi, 2004). It is an acute phaseprotein, and is elevated in the event of tissue damage (surgery causesincreased CRP levels), inflammation and infection. It is produced andsecreted as a result of NFκβ cascade activation, and binds to pathogencell surfaces to allow complement binding. According to the inventionCRP may be detected by an immunoassay such as an ELISA (enzyme-linkedimmunosorbent assay). The invention thus provides an ELISA for detectingCRP in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human CRP) that specifically binds to CRP in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being mouse monoclonal anti-CRP        antibody) that specifically binds to CRP to the sample, which        reagent is conjugated to a label (such as biotin)    -   (c) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin)    -   (d) removing reagent not bound to the immunocapture surface    -   (e) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of CRP in the sample.

More specifically, the invention provides an ELISA for detecting CRP ina sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human CRP, catalogue number 842676 R&D systems) that        specifically binds to CRP in the sample (for a defined time such        as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as R&D diluent, catalogue number DY995        R&D systems) for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 100K in sample diluent PBS,        pH6.9, supplemented with 1% BSA incubated for a defined time        such as 2 hours    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being mouse anti CRP catalogue        number 842677 R&D systems) that specifically binds to CRP in the        sample, which reagent is conjugated to a label (such as biotin)        for a defined time such as 2 hours    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin,        catalogue number 890803 R&D systems) for a defined time such as        20 minutes    -   (j) Adding a substrate that initiates the colour change (such as        OPD, catalogue number P9187 Sigma-Aldrich)    -   (k) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of CRP in the sample with        a specified sensitivity (such as 15.6 pg/mL) and an assay range        (such as 1.56-100 μg/mL)

A schematic representation of a suitable assay format is shown in FIG.17A and a representative calibration curve for this assay is shown inFIG. 17B.

CRP may be detected in a lateral flow format in other embodiments. Theinvention thus provides a lateral flow assay for detecting CRP in asample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being anti-CRP Fab CA0001) that        specifically binds to CRP in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being anti-CRP Fab CA0001 antibody)        that specifically binds to CRP to the sample, which reagent is        conjugated to a label (such as a gold particle, optionally a 40        nm gold particle)    -   (c) measuring the levels of label at the immunocapture surface        as an indication of the levels of CRP in the sample.

More specifically, CRP may be detected in a lateral flow format in otherembodiments comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being mouse anti-CRP Fab CA0001 immobilised        at a concentration of 1 mg/mL) that specifically binds to CRP in        the sample    -   (b) addition of sample diluted 1 in 30 in sample diluent PBS,        pH6.9, supplemented with 1% (v/v) Tween 20+1% BSA    -   (c) CRP in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being mouse anti-CRP Fab CA0001 antibody),        which reagent is conjugated to a label (such as a gold particle,        optionally a 40 nm gold particle at 15 μg/mL in TAPS, pH8.5        buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of CRP in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete    -   (f) specified sensitivity (such as 3.9 ng/mL) and an assay range        (such as 19.5-1250 μg/mL)

A schematic representation of a suitable assay format is shown in FIG.18A and a representative calibration curve for this assay is shown inFIG. 18B. The following example components may be used:

Name Cat No Source Concentration Capture Anti CRP CA0001 Alere 1 mg/mLantibody Fab San Diego Detector Anti CRP Fab CA0001 Alere 15 μg/mLantibody 20 nm gold San conjugated Diego Control BSA biotin N/A Mologic0.25 mg/mL line Control Anti-biotin BA.GAB BBI OD2 gold gold StandardCRP 140-11R Lee 3.9-250 ng/mL Biosolutions

Another marker useful in the present invention is α1AT (alpha 1antitrypsin) a serine protease inhibitor which is synthesized in theliver, which is strongly associated with inhibition of neutrophilelastase. In this capacity it protects lung elastin from degradation byneutrophil elastase. α1AT deficiency potentially leads to COPD and liverdisease. Further to its protective anti-protease activity, α1AT isinvolved in inflammation and the immune response in the lung. It hasbeen shown to control the migration of neutrophils into the lung(Bergin, et al., 2010). α1AT was found to be significantly elevated inone study of neonatal sepsis (Suri, Thirupuram, & Sharma, 1991), andcould be used for predicting sepsis severity. According to the inventionα1AT may be detected by an immunoassay such as an ELISA (enzyme-linkedimmunosorbent assay). The invention thus provides an ELISA for detectingα1AT in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being        Fab 01521) that specifically binds to α1AT in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being Fab 01951) that specifically        binds to α1AT to the sample, which reagent is conjugated to an        enzyme (such as alkaline phosphatase)    -   (c) removing reagent not bound to the immunocapture surface    -   (d) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of α1AT in the sample.

More specifically, the provides an ELISA for detecting A1AT in a samplecomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human A1AT fab, catalogue number 01521 Alere San Diego)        that specifically binds to A1AT in the sample (for a defined        time such as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as PBS, pH6.9, supplemented with 1% BSA)        for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 200K in sample diluent PBS,        pH6.9, supplemented with 1% (v/v) Tween 20+1% BSA, incubated for        a defined time such as 1 hour    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being mouse anti-human A1AT fab,        catalogue number 01951 Alere San Diego) that specifically binds        to A1AT in the sample, which reagent is conjugated to a label        (such as alkaline phosphatase, catalogue number 702-0005, Innova        bioscience) for a defined time such as 1 hour    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding a substrate that initiates the colour change (such as        PNPP, catalogue number PNPP-001, Biopanda)    -   (j) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of A1AT in the sample        with a specified sensitivity (such as 260 pg/mL) and an assay        range (such as 0.28-260 μg/mL)

A schematic representation of a suitable assay format is shown in FIG.19A and a representative calibration curve for this assay is shown inFIG. 19B.

The following example components may be used:

Name Cat No Source Concentration Capture Anti A1AT 01521 Alere San 4μg/mL antibody Fab Diego Detector Anti A1AT 01951 Alere San AP antibodyFab AP Diego conjugated Standard A1AT 178251 Calbiochem 0.26-160 ng/mL

α1AT may be detected in a lateral flow format in other embodiments. Theinvention thus provides a lateral flow assay for detecting α1AT in asample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being Fab 01951) that specifically binds to        α1AT in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being Fab 01521) that specifically        binds to α1AT to the sample, which reagent is conjugated to a        label (such as a gold particle, optionally a 40 nm gold        particle)    -   (c) measuring the levels of label at the immunocapture surface        as an indication of the levels of α1AT in the sample.

More specifically, A1AT may be detected in a lateral flow format inother embodiments, comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being mouse anti-A1AT Fab 01951 Alere San        Diego, immobilised at a concentration of 1 mg/mL) that        specifically binds to A1AT in the sample    -   (b) addition of sample diluted 1 in 200K in sample diluent PBS,        pH6.9, supplemented with 1% (v/v) Tween 20+1% BSA    -   (c) A1AT in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being mouse anti-A1AT Fab 01521 antibody, Alere        San Diego), which reagent is conjugated to a label (such as a        gold particle, optionally a 40 nm gold particle at 15 μg/mL in        Borate, pH9.3 buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of A1AT in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete    -   (f) specified sensitivity (such as 260 pg/mL) and an assay range        (such as 0.26-160 μg/mL)

A schematic representation of a suitable assay format is shown in FIG.20A and a representative calibration curve for this assay is shown inFIG. 20B.

The following example components may be used:

Name Cat No Source Concentration Capture Anti 01951 Alere San 1 mg/mLantibody A1AT-BSA Diego Fab Detector Anti A1AT 01521 Alere San 15 μg/mLantibody Fab gold Diego conjugated Control BSA biotin N/A Mologic 0.25mg/mL line Control Anti-biotin BA.GAB BBI OD2 gold gold Standard A1AT178251 Calbiochem 0.44-360 ng/mL

Another marker useful in the present invention is TNFα, a cytokine andmembrane bound protein involved in inflammation, apoptosis and lipidmetabolism. It is shed from cell membranes by TACE/ADAM17 to yield TNFαcytokine. It is implicated in a variety of diseases, includingautoimmune diseases, cancer and sepsis. It is its role in inflammationwhich implicates TNFα in sepsis, it is important in recruitinginflammatory cells to sites of infection. TNFα has been shown to beelevated in patients with sepsis, and has been shown to be higher inpatients who died of sepsis than patients who recovered (Gogos, Drosou,Bassaris, & Skoutelis, 2000). Anti-TNFα is used as a treatment forRheumatoid Arthritis and Crohn's disease. There has been workinvestigating the effectiveness of anti-TNFαas treatment for sepsis, andwas found to reduce mortality in patients with severe sepsis, but notpatients in septic shock or with elevated IL-6 levels (Lv, Han, Yi,Kwon, Dai, & Wang, 2014), though this contradicts other reports thatblocking TNFα doesn't improve mortality rates in cases of sepsis.According to the invention TNFα may be detected by an immunoassay suchas an ELISA (enzyme-linked immunosorbent assay). The invention thusprovides an ELISA for detecting TNFα in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human TNFα) that specifically binds to TNFα in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being polyclonal TNFα antibody)        that specifically binds to TNFα to the sample, which reagent is        conjugated to a label (such as biotin)    -   (c) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin)    -   (d) removing reagent not bound to the immunocapture surface    -   (e) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of TNFα in the sample.

More specifically, the invention also provides an ELISA for detectingTNFα in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human TNFα, catalogue number 840119 R&D systems) that        specifically binds to TNFα in the sample (for a defined time        such as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as R&D diluent, catalogue number DY995        R&D systems) for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 2 in sample diluent PBS,        pH6.9, supplemented with 1% BSA incubated for a defined time        such as 2 hours    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being goat polyclonal TNFα antibody        catalogue number 840121 R&D systems) that specifically binds to        TNFα in the sample, which reagent is conjugated to a label (such        as biotin) for a defined time such as 2 hours    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin,        catalogue number 893975 R&D systems) for a defined time such as        20 minutes    -   (j) Adding a substrate that initiates the colour change (such as        OPD, catalogue number P9187 Sigma-Aldrich)    -   (k) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of TNFα in the sample        with a specified sensitivity (such as 15.6 pg/mL) and an assay        range (such as 31.2-2000 pg/mL)

A schematic representation of a suitable assay format is shown in FIG.21A and a representative calibration curve for this assay is shown inFIG. 21B.

TNFα may be detected in a lateral flow format in other embodiments. Theinvention thus provides a lateral flow assay for detecting TNFα in asample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being anti-TNFα shep antibody 579) that        specifically binds to TNFα in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being anti-TNFα BSA-Fab 01071) that        specifically binds to TNFα to the sample, which reagent is        conjugated to a label (such as a gold particle, optionally a 40        nm gold particle)    -   (c) measuring the levels of label at the immunocapture surface        as an indication of the levels of TNFα in the sample.

More specifically, TNFα may be detected in a lateral flow formatcomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being sheep anti-TNF catalogue number 579        Ig Innovations, immobilised at a concentration of 1 mg/mL) that        specifically binds to TNFα in the sample    -   (b) addition of sample (neat)    -   (c) TNFα in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being mouse anti-TNFα Fab 01071 antibody, Alere        San Diego), which reagent is conjugated to a label (such as a        gold particle, optionally a 40 nm gold particle at 20 μg/mL in        MES, pH5.3 buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of TNFα in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete    -   (f) specified sensitivity (such as 11 pg/mL) and an assay range        (such as 11-8000 pg/mL)

A schematic representation of a suitable assay format is shown in FIG.22A and a representative calibration curve for this assay is shown inFIG. 22B.

The following example components may be used:

Name Cat No Source Concentration Capture Sheep 579 Ig 1 mg/mL antibodypolyclonal Innovations anti-TNFα Detector Anti TNFα 01071 Alere San 20μg/mL antibody BSA-Fab Diego 40 nm gold conjugated Control line BSAbiotin N/A Mologic 0.25 mg/mL Control gold Anti-biotin BA.GAB BBI OD2gold Standard TNFα 840121 R&D 11-8000 pg/mL systems

Another marker useful in the present invention is IL-6, a cytokinedemonstrated to have a role in the immune response and in inflammation.It is elevated in infections and in chronic autoimmune diseases likerheumatoid arthritis. Pathogen Associated Molecular Patterns (PAMPs)bind to Pattern Recognition Receptors (PRRs) on macrophages, and inducethe NFκβ intracellular cascade which leads to IL-6 expression, and thesecretion of IL-6 as a pro-inflammatory cytokine. It is a pleiotropiccytokine, which is able to bind to IL-6 receptors and to the ubiquitousgp130 receptors when complexed to sIL-6R. As a part of the host responseto infection, IL-6 levels have been shown to be elevated in sepsispatients (Hack, et al., 1989). Furthermore IL-6 levels have been shownto correlate well to sepsis severity (Damas, et al., 1992). According tothe invention IL-6 may be detected by ELISA (enzyme-linked immunosorbentassay). The invention thus provides an immunoassay such as an ELISA fordetecting IL-6 in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human IL-6) that specifically binds to IL-6 in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being mouse polyclonal IL-6        antibody) that specifically binds to IL-6 to the sample, which        reagent is conjugated to a label (such as biotin)    -   (c) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin)    -   (d) removing reagent not bound to the immunocapture surface    -   (e) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of IL-6 in the sample.

More specifically, the invention also provides an ELISA for detectingIL-6 in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human IL-6, catalogue number 840113 R&D systems) that        specifically binds to IL-6 in the sample (for a defined time        such as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as R&D diluent, catalogue number DY995        R&D systems) for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 2 in sample diluent PBS,        pH6.9, supplemented with 1% BSA incubated for a defined time        such as 2 hours    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being goat polyclonal IL-6 antibody        catalogue number 840114 R&D systems) that specifically binds to        IL-6 in the sample, which reagent is conjugated to a label (such        as biotin) for a defined time such as 2 hours    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin,        catalogue number 893975 R&D systems) for a defined time such as        20 minutes    -   (j) Adding a substrate that initiates the colour change (such as        OPD, catalogue number P9187 Sigma-Aldrich)    -   (k) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of IL-6 in the sample        with a specified sensitivity (such as 9.4 pg/mL) and an assay        range (such as 18.75-1200 pg/mL)

A schematic representation of a suitable assay format is shown in FIG.23A and a representative calibration curve for this assay is shown inFIG. 23B.

IL-6 may be detected in a lateral flow format in other embodiments. Theinvention thus provides a lateral flow assay for detecting IL-6 in asample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being anti-IL6 Fab 11661 conjugated via PEG        to BSA) that specifically binds to IL-6 in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being polyclonal anti-IL6 antibody        AF-206-NA) that specifically binds to IL-6 to the sample, which        reagent is conjugated to a label (such as a gold particle,        optionally a 40 nm gold particle)    -   (c) measuring the levels of label at the immunocapture surface        as an indication of the levels of IL-6 in the sample.

More specifically, IL-6 may be detected in a lateral flow formatcomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being mouse anti-IL-6 fab conjugated to BSA        catalogue number 11661 Alere San Diego, immobilised at a        concentration of 3 mg/mL) that specifically binds to IL-6 in the        sample    -   (b) addition of sample (neat)    -   (c) IL-6 in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being goat anti-IL-6 antibody, Catalogue number        AF-206 R&D systems), which reagent is conjugated to a label        (such as a gold particle, optionally a 40 nm gold particle at 11        μg/mL in Borate, pH8.5 buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of IL-6a in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete    -   (f) specified sensitivity (such as 37.5 pg/mL) and an assay        range (such as 37.5-2400 pg/mL)

A schematic representation of a suitable assay format is shown in FIG.24A and a representative calibration curve for this assay is shown inFIG. 24B.

The following example components may be used:

Name Cat No Source Concentration Capture Anti IL6 11661 Alere 3 mg/mLantibody BSA Fab San Diego Detector Anti IL6 goat AF-206-NA R&D 11 μg/mLantibody polyclonal systems 40 nm gold conjugated Control BSA biotin N/AMologic 0.25 mg/mL line Control Anti-biotin BA.GAB BBI OD2 gold goldStandard IL6 840115 R&D 37.5-2400 pg/mL systems

Another marker useful in the present invention is PLA2G2A, aphospholipase which catabolises arachidonic acid. This enzymaticactivity releases bioactive breakdown products which act as modulatorsof inflammation, such as eicosanoids (the target of NSAIDs). PLA2G2A isinduced by a variety of cytokines, including IL-6 and TNFα (Crowl,Stoller, Conroy, & Stoner, 1991). Elevated PLA2G2A has been implicatedin atherosclerosis and rheumatoid arthritis. Polymorphisms in thePLA2G2A gene have been investigated, and certain polymorphisms werefound to predispose neonates to developing sepsis (Abu-Mazid, et al.,2010). According to the invention PLA2G2A may be detected by animmunoassay such as an ELISA (enzyme-linked immunosorbent assay). Theinvention thus provides an ELISA for detecting PLA2G2A in a samplecomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-PLA2G2A fab 01811) that specifically binds to PLA2G2A in        the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being anti-PLA2G2A 01671) that        specifically binds to PLA2G2A to the sample, which reagent is        conjugated to an enzyme (such as horseradish peroxidase)    -   (c) removing reagent not bound to the immunocapture surface    -   (d) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of PLA2G2A in the sample.

More specifically, the invention also provides an ELISA for detectingPLA2G2A in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human PLA2G2A fab, catalogue number 01811 Alere San Diego)        that specifically binds to PLA2G2A in the sample (for a defined        time such as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as PBS, pH6.9, supplemented with 1% BSA)        for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 10 in sample diluent PBS        supplemented with 50% hispec assay diluent (BioRad), 10% FCS and        0.4% BSA, incubated for a defined time such as 1 hour    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being mouse anti-human PLA2G2A fab,        catalogue number 01671 Alere San Diego) that specifically binds        to PLA2G2A in the sample, which reagent is conjugated to a label        (such as horse radish peroxidase, catalogue number 702-0000,        Innova bioscience) for a defined time such as 1 hour    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding a substrate that initiates the colour change (such as        OPD, catalogue number P9187 Sigma-Aldrich)    -   (j) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of PLA2G2A in the sample        with a specified sensitivity (such as 0.78 ng/mL) and an assay        range (such as 7.8-500 ng/mL)

A schematic representation of a suitable assay format is shown in FIG.25A and a representative calibration curve for this assay is shown inFIG. 25B.

The following example components may be used:

Name Cat No Source Concentration Capture Mouse Anti- 01811 Alere 2 μg/mLantibody PLA2G2A San fab Diego Detector Mouse Anti- 01671 Alere 100ng/mL antibody PLA2G2A San fab Diego Standard PLA2G2A 5374-PL- R&D0.78-50 ng/mL 010 Systems

PLA2G2A may be detected in a lateral flow format in other embodiments.The invention thus provides a lateral flow assay for detecting PLA2G2Ain a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being anti-PLA2G2A fab 01671 conjugated via        PEG to BSA) that specifically binds to PLA2G2A in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being anti-PLA2G2A 01811 BSA-Fab)        that specifically binds to PLA2G2A to the sample, which reagent        is conjugated to a label (such as a gold particle, optionally a        40 nm gold particle)    -   (c) measuring the levels of label at the immunocapture surface        as an indication of the levels of PLA2G2A in the sample.

More specifically, PLA2G2A may be detected in a lateral flow formatcomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being mouse anti-PLA2G2A fab catalogue        number 01671 Alere San Diego, immobilised at a concentration of        1.5 mg/mL) that specifically binds to PLA2G2A in the sample    -   (b) addition of sample (neat)    -   (c) PLA2G2A in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being mouse anti-IL-6 antibody, Catalogue        number 01811 Alere San Diego), which reagent is conjugated to a        label (such as a gold particle, optionally a 40 nm gold particle        at 10 μg/mL in TAPS, pH8.5 buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of PLA2G2A in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete    -   (f) specified sensitivity (such as 2 ng/mL) and an assay range        (such as 2-500 ng/mL)

A schematic representation of a suitable assay format is shown in FIG.26A and a representative calibration curve for this assay is shown inFIG. 26B.

The following example components may be used:

Name Cat No Source Concentration Capture Anti PLA2G2A 01671 Alere 1.5mg/mL antibody BSA Fab San Diego Detector Anti PLA2G2A 01811 Alere 10μg/mL antibody BSA Fab San 40 nm gold Diego conjugated Control BSAbiotin N/A Mologic 0.25 mg/mL line Control Anti-biotin BA.GAB BBI OD2gold gold Standard PLA2G2A 5374-PL-010 R&D 2-500 ng/mL Systems

Another marker useful in the present invention is sICAM1 the cell-free,circulating version of ICAM1. ICAM1 interacts with LFA-1 to contributetowards T-cell activation and leukocyte endothelial migration. sICAM1competitively binds LFA-1, preventing the LFA-1/ICAM1 complex forming(Meyer, Dustin, & Carron, 1995), reducing T-cell activation. sICAM1 hasbeen implicated in a variety of diseases. sICAM1 levels have been linkedto Blood Brain Barrier Dysfunction following traumatic injury, this isthought to be mediated by induction of MIP-2 (Otto, Heinzel-Pleines,Gloor, Trentz, Kossmann, & Morganti-Kossmann, 2000). Elevated sICAMlevels have also been found in cardiovascular disease (Jenny, et al.,2006) and breast cancer (Merendino, et al., 2001). sICAM1 levels werefound to be elevated in patients with Sepsis related Multiple OrganFailure (MOF) compared with patients with sepsis but without MOF,suggesting it may be a marker of disease severity (Endo, et al., 1995).According to the invention sICAM1 may be detected by an immunoassay suchas an ELISA (enzyme-linked immunosorbent assay). The invention thusprovides an ELISA for detecting sICAM1 in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human ICAM1) that specifically binds to sICAM1 in the        sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being mouse mouse monoclonal        anti-ICAM-1 antibody) that specifically binds to sICAM1 to the        sample, which reagent is conjugated to a label (such as biotin)    -   (c) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin)    -   (d) removing reagent not bound to the immunocapture surface    -   (e) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of sICAM1 in the sample.

More specifically, the invention also provides an ELISA for detectingsICAM-1 in a sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an ELISA plate) on which is immobilised a reagent (such as an        antibody, as defined herein, one specific example being mouse        anti-human sICAM-1, catalogue number 840432 R&D systems) that        specifically binds to CRP in the sample (for a defined time such        as overnight)    -   (b) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (c) blocking unbound sites on the surface with the addition of a        blocking solution (such as R&D diluent, catalogue number DY995        R&D systems) for a defined time such as 1 hour.    -   (d) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (e) addition of sample diluted 1 in 500 in sample diluent PBS,        pH6.9, supplemented with 1% BSA incubated for a defined time        such as 2 hours    -   (f) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (g) adding a further reagent (such as an antibody, as defined        herein, one specific example being Sheep anti sICAM-1 catalogue        number 840433 R&D systems) that specifically binds to sICAM-1 in        the sample, which reagent is conjugated to a label (such as        biotin) for a defined time such as 2 hours    -   (h) removing reagent not bound to the immunocapture surface with        a wash step (wash buffer 50 mM tris buffered saline pH8,        supplemented with 0.1% (v/v) Tween 20)    -   (i) Adding an enzyme (such as horseradish peroxidase) conjugated        to a binding partner for the label (for example streptavidin,        catalogue number 893975 R&D systems) for a defined time such as        20 minutes    -   (j) Adding a substrate that initiates the colour change (such as        OPD, catalogue number P9187 Sigma-Aldrich)    -   (k) measuring the levels of enzyme activity at the immunocapture        surface as an indication of the levels of sICAM-1 in the sample        with a specified sensitivity (such as 31.2 pg/mL) and an assay        range (such as 15.6-1000 ng/mL)

A schematic representation of a suitable assay format is shown in FIG.27A and a representative calibration curve for this assay is shown inFIG. 27B.

sICAM1 may be detected in a lateral flow format in other embodiments.The invention thus provides a lateral flow assay for detecting sICAM1 ina sample comprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being anti-sICAM-1 sheep antibody CF 1635)        that specifically binds to sICAM1 in the sample    -   (b) adding a further reagent (such as an antibody, as defined        herein, one specific example being anti-sICAM-1 Fab 1461) that        specifically binds to sICAM1 to the sample, which reagent is        conjugated to a label (such as a gold particle, optionally a 40        nm gold particle)    -   (c) measuring the levels of label at the immunocapture surface        as an indication of the levels of sICAM1 in the sample.

More specifically, sICAM-1 may be detected in a lateral flow formatcomprising:

-   -   (a) contacting the sample with an immunocapture surface (such as        an immunocapture line on nitrocellulose membrane) on which is        immobilised a reagent (such as an antibody, as defined herein,        one specific example being sheep anti-sICAM-1 catalogue number        CF1635 Ig Innovations, immobilised at a concentration of 1        mg/mL) that specifically binds to sICAM-1 in the sample    -   (b) addition of 1 in 30 in sample diluent PBS, pH6.9,        supplemented with 1% (v/v) Tween 20+1% BSA    -   (c) sICAM-1 in the sample complexes with a reagent present in        conjugate pad (such as an antibody, as defined herein, one        specific example being mouse anti-IL-6 antibody, Catalogue        number 1461 Alere San Diego), which reagent is conjugated to a        label (such as a gold particle, optionally a 40 nm gold particle        at 15 μg/mL in TAPS, pH8.5 buffer)    -   (d) measuring the levels of label at the immunocapture surface        as an indication of the levels of sICAM-1 in the sample after a        specific read time (such as 10 minutes) with an        immunochromatographic reader.    -   (e) A control system such as an BSA biotin capture (immobilised        at a concentration of 0.25 mg/mL) and an anti-biotin gold        conjugate (catalogue number BA.GAB, BBI at OD2) indicates that        the test is complete    -   (f) specified sensitivity (such as 42 ng/mL) and an assay range        (such as 0.042-32 μg/mL)

A schematic representation of a suitable assay format is shown in FIG.28A and a representative calibration curve for this assay is shown inFIG. 28B.

The following example components may be used:

Name Cat No Source Concentration Capture Anti sICAM-1 CF1635 Ig 1 mg/mLantibody Sheep antibody innova- tions Detector Anti sICAM-1 1461 Alere15 μg/mL antibody Fab 40 nm San gold conjugated Diego Control BSA biotinN/A Mologic 0.25 mg/mL line Control Anti-biotin BA.GAB BBI OD2 gold goldStandard sICAM1 PR21065 Alere 1.4-1000 ng/mL San Diego

According to all aspects of the invention levels of the at least one,two or three markers may be calculated with reference to a thresholdlevel of each marker. The threshold levels may be adapted (orpersonalised) to the subject. The invention may therefore rely upon apersonalised baseline level of the relevant marker or markers againstwhich the threshold is calculated. Calculation may be on an on-goingbasis to coincide with testing. Thus, the threshold may be a rollingthreshold derived from the rolling baseline. In this context, it isapparent that levels of the marker or markers do not have to be measuredin absolute terms and may be measured in absolute or relative terms. Themarkers simply have to be measured in a manner which permits acomparison to be made with marker levels in samples taken at differenttime points. Alternatively, the threshold level for each marker may beset based on a population analysis. The threshold level may be set tomaximise sensitivity and/or specificity of detection as would be readilyappreciated by one skilled in the art.

In some embodiments, the threshold level of the marker is set bydetermining the levels of the marker in samples taken from the subjectat earlier time points (such as before surgery). In its simplest form,the invention may rely upon a simple comparison between the test sampleand the level of the marker in the previously taken sample (i.e. asingle earlier time point). However, the earlier time points maycomprise at least two, and possibly 3, 4, 5, 6, 7, 8, 9, 10 etc, earliermeasurements immediately preceding the determination of the level of themarker in the current sample.

Where marker levels are measured at multiple time points those levelsmay be averaged to provide the threshold for the test sample, abovewhich a SIRS and/or sepsis is predicted or identified. In someembodiments, the threshold may be set with reference to a sliding windowwithin which levels of the markers have been measured to provide abaseline. The threshold level is thus “learned” by the system. It is nota fixed threshold and is adapted to the subject, thereby taking intoaccount insignificant fluctuations in marker levels from the baselinethat are not predictive or indicative of SIRS and/or sepsis.Accordingly, the threshold may be set around the baseline to specify anallowable range of the marker levels beyond which a statisticallysignificant increase (or decrease) in level is indicated. In thepresence of drift of the baseline level of the marker, it is possiblethat the parameter limits may be narrowed such that a further change inlevel of the markers is deemed significant. For example, if the baselinemarker level is drifting upwards over time, the difference between ameasured increase and baseline may need to be smaller (compared to thesituation in which the baseline is relatively stable) to be consideredto have exceeded the threshold (i.e. to be significant). For example, adifference from baseline of at least 5, 10, 15, 20% or more may beconsidered significant generally. This difference may be reduced ifthere have been multiple previous measurements displaying a trendupwards or downwards but in each case by an amount less than thethreshold difference. The difference (in order to be consideredsignificant) may thus be reduced to at least 1, 2, 3, 4, 5% or more asappropriate in the event of a drift upwards or downwards in thebaseline.

The threshold may be set in relation to multiple markers as discussed ingreater detail herein. Thus, the prediction or diagnosis of SIRS and/orsepsis may be identified based upon a deviation from baseline that iscumulative according to the multiple markers measured. Typically,however, each marker will be measured individually with reference to amarker specific baseline and against a marker specific threshold. It isshown herein that use of multiple individual markers provides animproved ability to predict or diagnose SIRS and/or sepsis. Thus, theinvention may rely upon a plurality of baselines/thresholds dependingupon the individual markers employed. The methods and systems may weightthe contribution of a plurality of markers.

Because the present invention relies upon measuring the levels ofmultiple markers, the final prediction or identification or sepsisand/or SIRS requires that the measured levels are integrated, ideally toprovide a simply binary result that is readily interpreted. A suitablealgorithm may be employed in order to interpret the data from the levelsof the at least three markers and apply it to provide the prediction ordiagnosis. In some embodiments, the marker levels may be inter-dependentand thus the algorithm is based on this predicted relationship. Incertain embodiments, the determined levels of the at least three (ormore) markers are analysed in a pre-determined sequence to monitor thesubject. This may give rise to a decision tree, as explained furtherherein to predict or diagnose sepsis and/or SIRS. The levels of thefirst of the multiple markers may influence the subsequent thresholdsrequired for the other markers in order to predict or diagnose sepsisand/or SIRS, as would readily be appreciated by one skilled in the art.The output of the methods may also guide future sampling and treatmentof the subject. Thus, in some embodiments, for a given sample, themarker levels may be analysed in sequence until a marker is found withan increased level (or all markers have been examined). If a marker isdetected at increased level the further markers may or may not also beassessed to determine if their level is also increased. The likelihoodof SIRS and/or sepsis may be higher in the event that multiple markersare increased in a sample and the algorithm may account for this in theoutcome, e.g. by weighting the observations. Thus, the sample may be“graded” based upon how many of the markers are increased in levelcompared to threshold. For example, Grade 1 may indicate only one of themarkers is increased in the sample, Grade 2 may indicate two of themarkers is increased etc. Grade 3 or above may predict or diagnose SIRSand/or sepsis. Alternatively, the presence of an increased level of onemarker is enough to predict or diagnose sepsis (and/or SIRS) but anincreased level of one, two or more further markers increases theconfidence level of the prediction or diagnosis.

In some embodiments, the determined levels of the at least three markersare weighted. Weighting is a well-known method of applying a degree ofrelative significance to the multiple markers. The algorithm may be athreshold based algorithm as discussed herein.

The levels of the measured markers may be combined using logisticregression, decision tree analysis, neural networks and/or machinelearning. Logistic regression analysis involves formulating astatistical model which adds different markers together in a weightedfashion. Similar to linear regression which can be resolved using theequation y=mx+c, logistic regression allows for the addition of multiplemarkers and only allows for a binary outcome so the y is replaced withthe logit (defined as the In(odds) of being in the positive outcomegroup). Mathematically, the logistic regression equation islogit=(βnXn)+c. This uses quantitative data of all markers in a weightedfashion in the calculation.

In decision tree analysis, an individual is assessed for one marker at atime until they reach a terminal node which classifies the patient intothe positive or negative outcome group. This uses cut-off values foreach individual marker and does not necessarily use all markers in thealgorithm, depending upon at which point they are categorised.

Use of neural network displays some similarity to logistic regression inthat each node is a summation of the input (marker) multiplied by aweighting (beta coefficient). However, summation is performed a numberof times; there are a number of nodes and the input to these nodes canbe nodes themselves rather than the measured levels. The nodes are firstentered at random with random weights, the difference between theexpected output and the observed output is then calculated. If it is not0 (which is likely to be the case) the weightings are altered in thepreceding layer and then in the layer before that until the inputvariables are reached. The outputs are recalculated and the differencesare calculated again, and the model weighting readjusted. This cancontinue indefinitely until the difference in expected and observedoutputs is minimal.

In specific embodiments, where sepsis is diagnosed or predicted thesubject is treated. Suitable treatments for sepsis are known in the art.They include antibiotics as discussed in more detail herein. The subjectmay continue monitoring during treatment in order to assess theeffectiveness of the treatment.

The invention may be performed using systems or test kits as describedherein. The invention may be performed using a testing device, testingkit or testing composition of matter as described herein.

The invention also relates to the computer applications used in thesystems and test kits. The computer applications may also be used in thetesting devices, testing kits or testing composition of mattersdescribed herein (in particular that incorporate a reader). Thus, incertain embodiments, the computer-implemented method, system, andcomputer program product may be embodied in a computer application, forexample, that operates and executes on a processor, such as in thecontext of a computing machine.

As used herein, the processor may be comprised within any computer,server, embedded system, or computing system. The computer may includevarious internal or attached components such as a system bus, systemmemory, storage media, input/output interface, and a network interfacefor communicating with a network, for example.

The computer may be implemented as a conventional computer system, anembedded controller, a laptop, a server, a customized machine, any otherhardware platform, such as a laboratory computer or device, for example,or any combination thereof. The computing machine may be a distributedsystem configured to function using multiple computing machinesinterconnected via a data network or bus system, for example.

The processor may be configured to execute code or instructions toperform the operations and functionality described herein, managerequest flow and address mappings, and to perform calculations andgenerate commands. The processor may be configured to monitor andcontrol the operation of the components in the computing machine. Theprocessor may be a general purpose processor, a processor core, amultiprocessor, a reconfigurable processor, a microcontroller, a digitalsignal processor (“DSP”), an application specific integrated circuit(“ASIC”), a graphics processing unit (“GPU”), a field programmable gatearray (“FPGA”), a programmable logic device (“PLD”), a controller, astate machine, gated logic, discrete hardware components, any otherprocessing unit, or any combination or multiplicity thereof. Theprocessor may be a single processing unit, multiple processing units, asingle processing core, multiple processing cores, special purposeprocessing cores, co-processors, or any combination thereof. Accordingto certain example embodiments, the processor, along with othercomponents of the computing machine, may be a virtualized computingmachine executing within one or more other computing machines.

The storage medium may be selected from a hard disk, a floppy disk, acompact disc read only memory (“CD-ROM”), a digital versatile disc(“DVD”), a Blu-ray disc, a magnetic tape, a flash memory, othernon-volatile memory device, a solid-state drive (“SSD”), any magneticstorage device, any optical storage device, any electrical storagedevice, any semiconductor storage device, any physical-based storagedevice, any other data storage device, or any combination ormultiplicity thereof. The storage media may store one or more operatingsystems, application programs and program modules such as module, data,or any other information. The storage media may be part of, or connectedto, the computing machine. The storage media may also be part of one ormore other computing machines that are in communication with thecomputing machine, such as servers, database servers, cloud storage,network attached storage, and so forth.

The storage media may therefore represent examples of machine orcomputer readable media on which instructions or code may be stored forexecution by the processor. Machine or computer readable media maygenerally refer to any medium or media used to provide instructions tothe processor. Such machine or computer readable media associated withthe module may comprise a computer software product.

The input/output (“I/O”) interface may be configured to couple to one ormore external devices, to receive data from the one or more externaldevices, and to send data to the one or more external devices. Suchexternal devices along with the various internal devices may also beknown as peripheral devices. The I/O interface may include bothelectrical and physical connections for operably coupling the variousperipheral devices to the computing machine or the processor. The I/Ointerface may be configured to communicate data, addresses, and controlsignals between the peripheral devices, the computing machine, or theprocessor. The I/O interface may be configured to implement any standardinterface, such as small computer system interface (“SCSI”),serial-attached SCSI (“SAS”), fiber channel, peripheral componentinterconnect (“PCI”), PCI express (PCIe), serial bus, parallel bus,advanced technology attached (“ATA”), serial ATA (“SATA”), universalserial bus (“USB”), Thunderbolt, FireWire, various video buses, and thelike. The I/O interface may be configured to implement only oneinterface or bus technology.

Alternatively, the I/O interface may be configured to implement multipleinterfaces or bus technologies. The I/O interface may be configured aspart of, all of, or to operate in conjunction with, the system bus. TheI/O interface may include one or more buffers for bufferingtransmissions between one or more external devices, internal devices,the computing machine, or the processor.

The I/O interface may couple the computing machine to various inputdevices including mice, touch-screens, scanners, electronic digitizers,sensors, receivers, touchpads, trackballs, cameras, microphones,keyboards, any other pointing devices, or any combinations thereof. TheI/O interface may couple the computing machine to various output devicesincluding video displays, speakers, printers, projectors, tactilefeedback devices, automation control, robotic components, actuators,motors, fans, solenoids, valves, pumps, transmitters, signal emitters,lights, and so forth.

The computing machine may operate in a networked environment usinglogical connections through the network interface to one or more othersystems or computing machines across the network. The network mayinclude wide area networks (WAN), local area networks (LAN), intranets,the Internet, wireless access networks, wired networks, mobile networks,telephone networks, optical networks, or combinations thereof. Thenetwork may be packet switched, circuit switched, of any topology, andmay use any communication protocol. Communication links within thenetwork may involve various digital or an analog communication mediasuch as fiber optic cables, free-space optics, waveguides, electricalconductors, wireless links, antennas, radio-frequency communications,and so forth.

The processor may be connected to the other elements of the computingmachine or the various peripherals discussed herein through the systembus. It should be appreciated that the system bus may be within theprocessor, outside the processor, or both. According to someembodiments, any of the processor, the other elements of the computingmachine, or the various peripherals discussed herein may be integratedinto a single device such as a system on chip (“SOC”), system on package(“SOP”), or ASIC device.

Embodiments may comprise a computer program that embodies the functionsdescribed and illustrated herein, wherein the computer program isimplemented in a computer system that comprises instructions stored in amachine-readable medium and a processor that executes the instructions.However, it should be apparent that there could be many different waysof implementing embodiments in computer programming, and the embodimentsshould not be construed as limited to any one set of computer programinstructions. Further, a skilled programmer would be able to write sucha computer program to implement one or more of the disclosed embodimentsdescribed herein. Therefore, disclosure of a particular set of programcode instructions is not considered necessary for an adequateunderstanding of how to make and use embodiments. Further, those skilledin the art will appreciate that one or more aspects of embodimentsdescribed herein may be performed by hardware, software, or acombination thereof, as may be embodied in one or more computingsystems. Moreover, any reference to an act being performed by a computershould not be construed as being performed by a single computer as morethan one computer may perform the act.

The example embodiments described herein can be used with computerhardware and software that perform the methods and processing functionsdescribed previously. The systems, methods, and procedures describedherein can be embodied in a programmable computer, computer-executablesoftware, or digital circuitry. The software can be stored oncomputer-readable media. For example, computer-readable media caninclude a floppy disk, RAM, ROM, hard disk, removable media, flashmemory, memory stick, optical media, magneto-optical media, CD-ROM, etc.Digital circuitry can include integrated circuits, gate arrays, buildingblock logic, field programmable gate arrays (FPGA), etc.

The methods, systems, test kits, testing devices, testing kits andtesting compositions of matter may incorporate means for AutomaticIdentification and Data Capture (AIDC), such as a Radio-frequencyidentification tag or card (RIF)

For the avoidance of doubt, the discussion of the invention hereinaboveapplies to the systems, test kits, testing devices, testing kits andtesting compositions of matter of the invention and all embodiments canbe applied accordingly. However, for clarity and by way ofexemplification of how the discussion applies directly to the systems,test kits, testing devices, testing kits and testing compositions ofmatter, further specific embodiments are outlined below.

In some embodiments, the systems, test kits, testing devices, testingkits and testing compositions of matter take the form of a portablesystem. An example system upon which the various products of theinvention may be based is the Alere™ DDS®2 mobile test system. Thissystem comprises an analyser, into which a test cartridge is inserted.The user then also inserts a sample collection device into the analyser.The analyser incorporates a full colour screen to read the results. Theanalyser thus houses the processor and storage medium which permits theassays to be run. The test cartridge represents the one or more testingdevices for determining levels of the markers. The systems or test kitsof the invention may incorporate a separate sample collection device orthis may be integrated into the one or more testing devices.

In specific embodiments, the systems, test kits, testing devices,testing kits and testing compositions of matter further comprise adisplay for the output from the processor. This is intended to give asimple visual and/or audible read-out of the assays performed on thesample. The display may be operably connected to the processor runningthe computer application. The output or read-out may be an instructionto the subject in some embodiments. The output may be colour coded ornumerical to reflect the various possible outcomes of monitoring asdiscussed herein. It is possible for the display to provide levels ofthe markers measured in the sample and provide suitable training and/ordocumentation to assist the user in interpretation of the data. However,this is not preferred for obvious reasons of susceptibility to humanerror. A combination of both types of information may, however, bepresented in some embodiments. Thus, the display may present bothquantitative and qualitative read-outs in some embodiments. Probabilityvalues related to the predictive and identification outcomes may alsorepresent an output in some embodiments.

In specific embodiments, the one or more testing devices, testing kitsor testing compositions of matter comprise disposable single use devicesto which the sample is applied. Typically the one or more testingdevices, testing kits or testing compositions of matter may comprise asample receiving zone to which the sample is added. The devicestypically also incorporate a solid support which defines aliquid/capillary flow path for the sample once applied to the samplereceiving zone. The sample receiving zone may be an integral part of thesolid support. The solid support may comprise a chromatographic medium,such as a membrane material in some embodiments (e.g. nitrocellulose). Asample applied to the sample application zone will typically rehydratethe necessary reagents to detect the marker. The reagents includebinding reagents which specifically interact with the markers or asubstrate for effector molecules where activity is measured. Furtherreagents immobilized further along the flow path bind to the complex ofmarker and binding reagent. The binding reagent is labelled to provide asignal at the site of immobilization of the complex of marker andbinding reagent (through binding to the further reagent). Suitablelabels include fluorescent labels, magnetic labels, latex or gold aswould be readily understood by one skilled in the art.

When enzymatic activity is being assayed the binding reagent and/orfurther binding reagent may bind with a substrate only after it has beenmodified by the enzymatic activity, or may only bind if the substratehas not been modified by the enzymatic activity. Examples of enzymaticactivity assays include those set forth in International PatentApplications WO2009/024805, WO2009/063208, WO2007/128980, WO2007/096642,WO2007/096637, WO2013/156794, WO2015/059487 and WO2013/156795 (thecontent of each of which is hereby incorporated by reference).

The binding reagent and further reagent are typically antibodies (asdefined herein). Thus, in specific embodiments, the one or more testingdevices, testing kits or testing compositions of matter may comprise alateral flow test strip. In some embodiments, a single lateral flow teststrip is employed to permit detection of all markers that are to bedetermined in the test sample. In other embodiments, a separate lateralflow test strip is provided for each marker that is determined.

The devices, kits or compositions of matter may also include a controlzone to confirm sample has passed through the device satisfactorily. Inthe event this is not the case the system or test kit or reader of thetesting device, testing kit or testing composition of matter mayindicate an invalid result to the user, for example via the display. Thedevices, kits or compositions of matter may act as competitive orsandwich assays, as discussed herein. ELISA (enzyme linked immunosorbentassay) is an example of a suitable assay format that may be incorporatedin the testing devices used in the invention. Again, typically allreagents to detect the levels of the three or more markers arepre-loaded onto the testing device, kit or composition of matter suchthat they can interact with the sample once added to the device (forexample via the sample receiving zone). This minimizes intervention andthus error caused by the subject. Thus, effectively, the device may onlyrequire the user to apply the sample and subsequently observe the outputof the assay.

The systems, test kits, testing devices and testing compositions ofmatter may incorporate a suitable reader to provide a quantitativeoutput (in conjunction with the processor and storage medium). Asalready mentioned this output can be an absolute or a relative output.Suitable readers may incorporate an illuminator to expose the device toa specific wavelength or wavelengths of light and a suitable detectorfor the reflected or emitted light. The systems, test kits, testingdevices and testing compositions of matter may also incorporate asuitable processor and computer application to output the results basedupon the detected signal. Thus, the processor running the computerapplication will be in operable connection with the reader. By “operableconnection” is meant a functional connection that permits the exchangeof a signal or information between the elements.

As discussed above, where protein levels are measured the bindingreagent may comprise an antibody (to include derivatives, fragments andaptamers). Where RNA levels are measured suitable reagents may comprisenucleic acid amplification reagents such as primers, probes, dNTPs,polymerases etc. to permit amplification reactions to be run and resultsreported from the testing device.

The one or more testing devices, kits or compositions of matter maycomprise an enzyme detection device. These devices may be particularlyuseful for investigating enzymatic activity.

The system or test kit may incorporate the appropriate number of testingdevices to permit each marker to be determined. This is particularly thecase where the markers are detecting using different platforms. Thus, insome embodiments, the one or more testing devices comprise one or morelateral flow activity assays, ELISAs, fluorogenic substrate assays etc.In some embodiments, the one or more testing devices comprise one ormore lateral flow activity assays, ELISAs or competition assays. In someembodiments, the one or more testing devices comprise one or morelateral flow assays and ELISAs.

In certain embodiments, the computer application is configured to outputfrom the processor a diagnosis or prediction of SIRS and/or sepsis if anincrease in the levels of each of the at least 3, 4, 5, 6, 7, 8, 9, 10or more markers is calculated. In specific embodiments, the output is anindication that the subject should receive treatment.

It is also shown herein that certain markers are able to identify,within infected patients, the severity of the condition according toSOFA score. Thus, the invention also provides a method fordiscriminating a SOFA score of at least 2 from those with a SOFA scoreof less than 2 in a patient with systemic inflammatory response syndrome(SIRS) and an infection, the method comprising determining levels of atleast one, two, three or more markers selected from PLA2, CRP, CCL23,sICAM, IL-6, procalcitonin, A1AT, MMP8, TNFalpha, AcPGP, enzymatic MMPactivity, TIMP1, sRAGE and desmosine in a sample taken from the subject,wherein the combined levels of the at least three markers are used todiscriminate a patient with a SOFA score of at least 2 from a SOFA scoreof less than 2. It is preferred that the markers are selected from 1, 2,3, 4, 5, 6 or all of CCL23, A1AT, sICAM, desmosine, TNF alpha, IL-6 andPLA2g2A. The various systems, test kits, testing devices and testingcompositions of matter of the invention, as described herein, can beadapted to perform such methods as would be readily understood by oneskilled in the art.

DESCRIPTION OF THE FIGURES

FIG. 1 shows pie chart representations of the nature of infectionsdetected in the clinical samples

FIG. 2A shows the origins of infections in sepsis samples

FIG. 2B shows the origins of infections in sepsis samples infected withgram negative bacteria

FIG. 2C shows the origins of infections in sepsis samples infected withgram positive bacteria

FIG. 3 shows multiple ROC curves for the various assays performed on thesamples. The source of each curve is indicated.

FIG. 4 is a scatter plot showing the ability of the CRP, sICAM andTNFalpha marker combination to distinguish sepsis from controls in the Dsamples

FIG. 5 is a ROC curve showing the ability of the CRP, sICAM and TNFalphamarker combination to distinguish sepsis from controls in the D samples

FIG. 6A is a scatter plot showing the ability of the CRP, sICAM andTNFalpha marker combination to distinguish sepsis from controls in the Asamples

FIG. 6B is a box plot showing the ability of the CRP, sICAM and TNFalphamarker combination to distinguish sepsis from controls in the A samples

FIG. 7 is a ROC curve showing the ability of the CRP, sICAM and TNFalphamarker combination to distinguish sepsis from controls in the A samples

FIG. 8A is a scatter plot showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishsepsis from SIRS

FIG. 8B is a box plot showing the ability of the sICAM-1 (ELISA and LF),CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishsepsis from SIRS

FIG. 8C is a ROC curve showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishsepsis from SIRS

FIG. 9A is a scatter plot showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishSIRS from controls

FIG. 9B is a box plot showing the ability of the sICAM-1 (ELISA and LF),CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguish SIRSfrom controls

FIG. 9C is a ROC curve showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishSIRS from controls

FIG. 10A is a scatter plot showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishsepsis from controls

FIG. 10B is a box plot showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishsepsis from controls

FIG. 10C is a ROC curve showing the ability of the sICAM-1 (ELISA andLF), CCL23, A1AT, CRP, IL-6 and TNF-α marker combination to distinguishsepsis from controls

FIG. 11A shows levels of CRP over time in sepsis versus controls

FIG. 11B shows levels of IL-6 over time in sepsis versus controls

FIG. 11C shows levels of TIMP1 over time in sepsis versus controls

FIG. 11D shows levels of sICAM-1 over time in sepsis versus controls

FIG. 12 shows a point of care lateral flow device useful in the presentinvention

FIG. 13 sets out a possible personalised testing strategy that may beadopted according to the invention

FIG. 14 is a box plot showing the ability of sRAGE to distinguish sepsisfrom controls in the tested samples

FIG. 15A is a schematic representation of an ELISA assay format formeasuring levels of CCL23 in a sample

FIG. 15B shows a representative calibration curve for the ELISA assayformat for measuring levels of CCL23 in a sample

FIG. 16 is a schematic representation of a lateral flow assay format formeasuring levels of CCL23 in a sample

FIG. 17A is a schematic representation of an ELISA assay format formeasuring levels of CRP in a sample

FIG. 17B shows a representative calibration curve for the ELISA assayformat for measuring levels of CRP in a sample

FIG. 18A is a schematic representation of a lateral flow assay formatfor measuring levels of CRP in a sample

FIG. 18B shows a representative calibration curve for the lateral flowassay format for measuring levels of CRP in a sample

FIG. 19A is a schematic representation of an ELISA assay format formeasuring levels of A1AT in a sample

FIG. 19B shows a representative calibration curve for the ELISA assayformat for measuring levels of A1AT in a sample

FIG. 20A is a schematic representation of a lateral flow assay formatfor measuring levels of A1AT in a sample

FIG. 20B shows a representative calibration curve for the lateral flowassay format for measuring levels of A1AT in a sample

FIG. 21A is a schematic representation of an ELISA assay format formeasuring levels of TNFalpha in a sample

FIG. 21B shows a representative calibration curve for the ELISA assayformat for measuring levels of TNFalpha in a sample

FIG. 22A is a schematic representation of a lateral flow assay formatfor measuring levels of TNFalpha in a sample

FIG. 22B shows a representative calibration curve for the lateral flowassay format for measuring levels of TNFalpha in a sample

FIG. 23A is a schematic representation of an ELISA assay format formeasuring levels of IL-6 in a sample

FIG. 23B shows a representative calibration curve for the ELISA assayformat for measuring levels of IL-6 in a sample

FIG. 24A is a schematic representation of a lateral flow assay formatfor measuring levels of IL-6 in a sample

FIG. 24B shows a representative calibration curve for the lateral flowassay format for measuring levels of IL-6 in a sample

FIG. 25A is a schematic representation of an ELISA assay format formeasuring levels of PLA2G2A in a sample

FIG. 25B shows a representative calibration curve for the ELISA assayformat for measuring levels of PLA2G2A in a sample

FIG. 26A is a schematic representation of a lateral flow assay formatfor measuring levels of PLA2G2A in a sample

FIG. 26B shows a representative calibration curve for the lateral flowassay format for measuring levels of PLA2G2A in a sample

FIG. 27A is a schematic representation of an ELISA assay format formeasuring levels of sICAM1 in a sample

FIG. 27B shows a representative calibration curve for the ELISA assayformat for measuring levels of sICAM1 in a sample

FIG. 28A is a schematic representation of a lateral flow assay formatfor measuring levels of sICAM1 in a sample

FIG. 28B shows a representative calibration curve for the lateral flowassay format for measuring levels of sICAM1 in a sample

FIG. 29 shows a decision tree analysis of sepsis markers.

FIG. 30 shows diagnostic performance of the LR1 markers in terms ofdistinguishing the infection+SIRS group from the SIRS only group. FIG.30A is a scatter plot and FIG. 30B is a ROC curve.

FIG. 31 shows diagnostic performance of the LR2 markers in terms ofdistinguishing the infection+SIRS group from the SIRS only group basedon patients with SOFA scores of 2-6. FIG. 31A is a scatter plot and FIG.31B is a ROC curve.

FIG. 32 shows diagnostic performance of the LR2 markers in terms ofdistinguishing the infection+SIRS group from the SIRS only group acrossall patients, irrespective of SOFA score. FIG. 32A is a scatter plot andFIG. 32B is a ROC curve.

FIG. 33 shows diagnostic performance of the LR3 markers in terms ofdistinguishing high SOFA score from low SOFA score in the infected groupto indicate severity (sepsis). FIG. 33A is a scatter plot and FIG. 33Bis a ROC curve.

FIG. 34 is a scatter plot showing that the LR2 algorithm was able topositively identify the infected patients in the validation set (basedon day 0 samples).

FIG. 35 is a timecourse showing that the LR2 algorithm could also beused to discriminate survivors from non-survivors.

EXAMPLES

The invention will be further understood with reference to the followingexperimental examples.

Example 1—Improving on CRP for sepsis diagnosis SUMMARY Background

Although many new biomarkers for sepsis diagnosis have beeninvestigated, to be useful in clinical practice, and to improvesensitivity and specificity it may be necessary to combine them withtraditional markers, particularly C-reactive protein (CRP). This studycompared the diagnostic accuracy of CRP used alone and in combinationwith selected complementary markers for the diagnosis of sepsis.

Methods

One hundred and two patients diagnosed with sepsis based on strictclinical criteria including positive blood cultures (51 withGram-positive, 49 Gram-negative and 2 mixed Gram-positive andGram-negative microorganisms) were compared to 102 patients with noevidence of sepsis. Serum levels were measured for CRP and procalcitonin(PCT), as well as seven selected potential markers. These comprised: twoinflammatory cytokines, interleukin-6 (IL-6) and tumour necrosis factoralpha (TNFα); the vascular marker soluble intercellular adhesionmolecule (sICAM-1); a chemokine, C—C motif ligand 23 (CCL23, also knownas macrophage inflammatory protein 3, MIP-3); secreted type IIAphospholipase (sPLA2g2a); matrix metalloprotease 8 (MMP8) and the serpinprotease inhibitor, α-1 antitrypsin (A1AT). The diagnostic accuracy ofeach marker alone was evaluated by receiver operator curve (ROC).Combinations of markers giving improved diagnostic performance wereidentified by logistic regression. Cut-off values and diagnosticalgorithms for marker combinations were developed by classification andregression tree analysis.

Findings

When markers were measured following confirmation of sepsis by positiveblood culture, the accuracy of CRP for sepsis diagnosis was superior tothat of the other markers investigated. sPLA2g2a was as sensitive asCRP, but its specificity was lower. Combining levels of sICAM-1 with CRPimproved diagnostic accuracy of CRP alone. When levels were measuredearlier, at the time the patient presented with symptoms of sepsis,sPLA2g2a displayed diagnostic accuracy equivalent to that of CRP. Anincrease in the diagnostic accuracy of CRP could be achieved bycombining measurement of CRP with sPLA2g2a.

Interpretation

Potential exists for improving the diagnostic accuracy of CRP in sepsisby combining measurement of its level with those of sPLA2g2a andsICAM-1. This approach would have value in supporting choice oftreatment options prior to confirmation by culture and inculture-negative cases where sepsis is suspected.

INTRODUCTION

Early and accurate diagnosis of sepsis is essential for initiation ofappropriate therapy. C-reactive protein (CRP) and procalcitonin (PCT)are the most widely used markers, but they have limited ability todistinguish between sepsis and systemic inflammatory response due tonon-infectious causes. Many other serum biological markers have beenevaluated for this purpose, including pro- and anti-inflammatorycytokines, chemokines, cell receptors for microbial toxins and cellularadhesion molecules.^(1,2) The underlying pathobiology of sepsis ispoorly understood and, owing to potential involvement of many organsystems, finding a specific marker that is reproducibly quantifiable inall septic patients has not been achieved. Currently, very fewserum-based tests are routinely used in the diagnosis of sepsis. CRP,and to a lesser extent PCT, are used in the diagnosis of sepsis but arewithout the high levels of sensitivity and specificity that are requiredto fully/confidently support clinical decisions. When considering apathology such as sepsis that has heterogeneous clinical presentations,the sensitivity and specificity of CRP and PCT might be improved bycombination with other biological markers, reflecting different aspectsof the host response to infection.^(3,4)

In this study we investigated whether combining a number of potentialmarkers with CRP would improve its diagnostic accuracy in patients withblood culture-confirmed systemic infection, using a group of age- andsex-matched hospital outpatients free from infection as controls. Thestudy was designed to select the optimum combination of markers, toestablish the cut-off levels for interpretation and re-assess theiraccuracy for the early diagnosis of sepsis. Serum was collectedfollowing patient consent and confirmation of systemic infection by apositive blood culture and, for a subgroup of patients, sera were alsoanalysed when symptoms of sepsis were first observed or when a septicpatient presented to our hospital. The markers studied comprised twocytokines: IL6 5 and TNFα;^(5,6) a chemokine (CCL23, also known asMIP3);⁷ the soluble intercellular adhesion molecule (sICAM1) reflectingthe vascular endothelial activation in infection;⁸ the tissue-degradingenzymes, matrix metalloprotease 8 (MMP8) and secreted type IIAphospholipase A2, PLA2g2a;^(9,10) and the protease inhibitor,al-antitrypsin (A1AT).¹¹ The use of each marker in sepsis diagnosis hasbeen previously reviewed by Pierrakos and Vincent.¹

Here, diagnostic accuracy of each marker was determined by area underthe receiver operator curve (AUROC), sensitivity and specificity.Potential for improving diagnostic accuracy by combining markers wasexplored by logistic regression analysis. Effective cut-off levels andtheir application in diagnostic algorithms were investigated byclassification and regression tree analysis. We examined the levels ofeach marker in serum collected following patient consent andconfirmation of sepsis by a positive blood culture. To investigate thevalue of the markers in detecting sepsis at an early stage, we alsomeasured marker levels in serum taken at intervals of one to eight days(median four days) prior to the time that symptoms of sepsis presented.This was carried out for 44 patients where surplus samples wereavailable from measurement of other clinical parameters.

Methods

Patients

Serum samples were obtained from evaluable adult patients who had beensuffering from SIRS.¹² All the patients had been acutely unwell for aduration of no more than five days and had positive blood cultures. Allthe patients' clinical details were reviewed independently by twoConsultant Microbiologists (TE and MD) at the University HospitalsBirmingham NHS Foundation Trust and the blood culture isolates wereconsidered to represent significant bacteraemia. Sepsis was defined asSIRS in the presence of a confirmed infection. Criteria for SIRS weretemperature <36.6° C. or 38° C. and white cell count <4.0×10⁹/L or>12.0×10⁹/L. Bacteremia was confirmed in all sepsis patients by positiveblood cultures. The causative microorganism was identified byGram-staining and subculture onto appropriate media followed by routinebiochemical identification tests. Serum samples were collected from 98patients following patient consent and confirmation of sepsis by apositive blood culture. In addition, sera were obtained from 44 patientsat various time intervals during the course of their sepsis. These weresamples that had been taken for analysis of other blood markers as partof their routine clinical management. Samples were collected on the dayof onset of symptoms or admittance to hospital (when the initial bloodsamples were taken for culture). Controls comprised an age- andsex-matched group of patients attending an ophthalmic outpatient clinicat UHBFT. None had any evidence of sepsis in the preceding 12 weeks andno evidence of an inflammatory condition nor immunosuppression.

Study Approvals

Research Ethics committee (NRES West Midlands—Coventry and Warwickshire,REC ref: 12/WM/0251) and R&D Department (The University HospitalsBirmingham NHS Foundation Trust) approvals were obtained prior tocommencing the study. Informed written consent was received from all thestudy patients prior to participation in this study.

Marker Assays

Serum levels for IL-6, TNFα, sICAM-1, CCL23 and MMP8 were determined intriplicate using commercial ELISA kits (Duosets, R&D Systems, Abingdon,UK). PCT, PLA2 and A1AT were measured in triplicate by ELISA usingassays developed by Mologic Ltd. CRP levels were determined byparticle-enhanced immunoturbidimetry (Roche Diagnostics, Burgess Hill,West Sussex, UK) by Clinical Biochemistry at University HospitalsBirmingham NHS Foundation Trust.

Statistical Analysis

Descriptive statistics were calculated using Prism vs6 (GraphPad). TheD'Agostino-Pearson omnibus normality test was used to check whethermarker values followed a Gaussian distribution. The diagnostic accuracyof each marker to distinguish between sepsis and controls was determinedas the area under the receiver operator curve (AUROC, sensitivity vs1-specificity). Optimum cut-off levels for each marker used alone werecalculated from the ROC curves at the maximum value of the Youden index(J=sensitivity+specificity−1). Forward stepwise logistic regression wasused to investigate the value of combinations of markers in theprediction of sepsis (SPSS vs20.0, IBM). Classification and regressiontree analysis was used to construct diagnostic algorithms by sequentialapplication of marker cut-off values (SPSS).

Results

The sepsis group comprised 102 patients, age range 20-97 years, mean59.0 years, M/F 52/48. The sources of sepsis were; intravascular (IV)catheters (32), abdominal and biliary (21), renal and urinary (17), skinand soft tissue (15), respiratory (7), non-IV catheter vascular (5) andother/unknown (5). Causative organisms identified from blood wereGram-negative bacteria (51), Gram-positive bacteria (49) and 2 mixedGram-positive and Gram-negative bacteria (2). Bacterial species aregiven in Table 1. The control group comprised 102 individuals, age range23-88 years, mean 60.6 years, M/F 55/47. Median marker levels in serataken from 98 patients following patient consent and confirmation ofsepsis by a positive blood culture, and from controls are shown in Table2. Because the marker levels were not normally distributed, thesignificance of the difference in median marker levels between sepsisand controls was determined by the Mann-Whitney U test. Performance ofeach marker in the diagnosis of sepsis was summarised as the area underthe ROC curve (AUROC). The cut-off levels giving optimum diagnosticaccuracy for each marker were determined at the maximum value of theYouden index on the ROC curves, sensitivity and specificity at thiscut-off are listed in Table 2. Individually, CRP gave the clearestdiagnosis of sepsis, followed by sPLA2g2a and sICAM-1, each marker beingmore accurate than PCT in terms of AUROC, sensitivity and specificity.IL6 and CCL23 gave poor specificity and sensitivity respectively, whilstthe other markers were of very limited diagnostic value. To investigatewhether different diagnostic performance would be obtained from samplestaken earlier in the septic episode, marker levels were measured in seraat the time of the onset of symptoms of sepsis. These marker levels werecompared with the marker levels from the serum taken following patientconsent and confirmation of sepsis by a positive blood culture. OnlyIL6, PLA2g2a, TNFα and CCL23 showed significant differences (MannWhitney p values <0.0001, 0.0191, 0.0384 and 0.0025 respectively),suggesting that these markers might provide better diagnostic accuracywhen measured in samples taken early in the course of sepsis. Diagnosticaccuracy of each of the markers was therefore assessed as before, usingthe earlier time samples for the 44 patients and 102 controls. Theresults are shown in Table 3. The median time between the early samples(Table 3) and those taken when blood cultures were positive (Table 2)was four days (mean=4.038, SD=1.311, SEM=0.2571), minimum one day (onepatient), maximum eight days (one patient), 25% percentile 3.75 days,75% percentile five days. CRP and PLA2g2a showed the best diagnosticaccuracy in terms of sensitivity at the optimum cut-off. Comparing thedata in Tables 2 and 3 shows a notable improvement in diagnosticaccuracy of IL6 and CCL23 when their levels are measured at the earlierstage of sepsis. This indicates their early production and subsequentreduction during the course of sepsis.

The value of combining markers with CRP to improve its diagnosticperformance was explored by binary logistic regression. Logisticregression models were derived by entering each marker separately withCRP. The predictive performance of each model was then compared withthat of CRP alone (Table 4). Using the marker levels from serumfollowing patient consent and confirmation of sepsis by a positive bloodculture, only sICAM-1 provided a logistic regression model that improvedon the performance of CRP alone in both sensitivity and specificity.Whereas CRP alone correctly identified 92/98 sepsis patients and 99/102controls, combination of sICAM-1 with CRP in the logistic regressionmodel correctly identified 95/98 sepsis and 100/102 controls. When allmarkers were submitted to forward stepwise (likelihood ratio) logisticregression a model giving 96% sensitivity and 99% specificity wasproduced, based on combination of CRP, sICAM-1, IL6 and sPLA2g2a. Usingthe same approach for marker levels measured at the onset of sepsissymptoms, combination of PLA2 with CRP gave the greatest improvement inperformance. Addition of this marker improved the diagnostic performanceof CRP from 40/44 sepsis patients and 101/102 controls correctlyidentified to 43/44 sepsis patients and 101/102 controls. Separatecombinations of either PCT, sICAM-1, IL6 or CCL23 with CRP also improvedsensitivity from 40/44 sepsis to 41/44 without loss of specificity. Whenall markers were submitted to forward stepwise (likelihood ratio)logistic regression a model was produced based on combination of CRP,sICAM-1, IL6 and sPLA2g2a.

Combination of markers with CRP in diagnostic algorithms was alsoinvestigated by classification and regression tree analysis (CART). Forthe marker levels taken following patient consent and confirmation ofsepsis by a positive blood culture, where combination of sICAM-1 withCRP improved the sensitivity by logistic regression, the initialapplication of sICAM-1 at a cut-off level of 302 μg/L correctlyidentified 68/98 sepsis patients with no false positives (i.e. nocontrols above this cut-off level). Application of a CRP cut-off levelof 20.5 mg/L to the remaining samples (those with sICAM-1 levels below302 μg/L, comprising 32 sepsis patients and 102 controls) correctlyidentified a further 29/32 sepsis patients with one false positive,leaving 101/102 controls with marker levels below the cut-off values forboth markers. Overall sensitivity for this group of samples wastherefore 99% with 99% specificity, compared with 92% and 97% for CRPalone. For the smaller number of samples analysed at the time of onsetof sepsis symptoms, where logistic regression showed sPLA2g2a to improvethe accuracy of CRP, CART analysis produced an algorithm involvingapplication of CRP at a cut-off level of 16.5 mg/L, followed by sPLA2g2aat a cut-off of 57.6 μg/L to those samples falling below this CRPcut-off. This algorithm correctly identified 42/44 sepsis patients withCRP above the cut-off level and three false positives. Application ofthe PLA2 cut-off to those samples falling below the CRP cut-offcorrectly identified the two remaining sepsis patients with noadditional false positives. The overall sensitivity was therefore 100%with a specificity of 97%, compared with 95% and 97% respectively withCRP alone.

When marker levels in patients with sepsis caused by Gram-positive andGram-negative bacteria were compared, only CRP showed a significantdifference in median levels. For the early onset samples, the CRP medianwas 113 mg/L (range 3-547) for Gram-positive sepsis (30), compared witha median CRP of 46 mg/L (range 4-42) for Gram-negative sepsis (12)(p=0.0005, Mann-Whitney U test). For samples taken following patientconsent and confirmation of sepsis by a positive blood culture, the CRPmedian levels were: 112 mg/L (range 7-550) for Gram-positive sepsis(49), compared with 69 mg/L (range 5-278) for Gram-negative sepsis (48)(p=0.0102). None of the other markers showed a significant differencebetween marker levels for Gram-positive and Gram-negative sepsis.

Mixed Gram-negative Gram-positive Gram-negative and -positive infection(n = 51) (n = 49) (n = 2) Staphylococcus aureus (25) Escherichia coli(28) E. coli and E. faecium (1) ‘Viridans’ streptococci (5) Pseudomonasaeruginosa (6) P. aeruginosa and ‘viridans’ Coagulase-negativestaphylococci (4) Klebsiella oxytoca (3) streptococci (1) Streptococcuspneumoniae (4) Stenotrophamonas maltophilia (3) Streptococcus pyogenes(4) Enterobacter aerogenes (1) Enterococcus faecium (1) Acinetobacterursingii (1) Enterococcus gallinarum (1) Klebsiella pneumoniae (1)Streptococcus agalactiae (2) Serratia marcescens (1) Group GStreptococci (2) Bacillus fragilis (1) Streptococcus constellatus (1)Salmonella sp. (1) Cardiobacterium hominis (1) E. coli and K. oxytoca(1) Coagulase-negative staphylococci E. coli and K. pneumoniae (1) andEnterococcus faecalis (1) K. pneumoniae and Enterobacter cloacae (1)

TABLE 2 Marker levels in sera from patients with sepsis (n = 98) andhealthy controls (n = 102). Markers were measured in sera takenfollowing patient consent and confirmation of sepsis by a positive bloodculture. sensitivity, 25% 75% specificity Marker group min percentilemedian percentile max p AUROC (cut-off) CRP control 0 0 0 3 29 <0.0001.992 94%, 97% mg/L sepsis 5 41.5 96.5 162.3 550 (18 mg/L) PCT control 00 0 0 2 <0.0001 .810 72%, 86% μg/L sepsis 0 0 2 6.5 75 (0.6 ng/L)sICAM-1 μg/L control 0 129.5 174.5 215.5 299 <0.0001 .883 85%, 87%sepsis 0 265 374.5 545 1039 (245 μg/L) IL6 control 0 0 3 21 982 <0.0001.772 84%, 67% ng/L sepsis 0 15.25 39.5 124 1779 (11 ng/L) sPLA2g2acontrol 0 8 14 22 80 <0.0001 .959 94%, 88% μg/L sepsis 8 47 102.5 266.8806 (32 μg/L) A1AT control 0 782 1360 2152 5831 0.0016 .628 66%, 49%μg/L sepsis 0 913 2028 3927 7989 (1314 mg/L) TNF control 0 0 0 27 28570.0127 .590 50%, 69% ng/L sepsis 0 0 0.5 154 2764 (3.2 ng/L) CCL23control 0 75 294 491 2969 <0.0001 .720 56%, 81% ng/L sepsis 0 282.5 7161374 7684 (570 ng/L) MMP8 control 0 6.25 11 18.75 49 0.0031 .623 63%,58% μg/L sepsis 0 6 17 37.5 43 (12.5 μg/L) p = probability, Mann-WhitneyU test. AUROC = area under the receiver operator curve (sensitivity vs1-specificity). Sensitivity and specificity determined at the optimumcut-off (maximum Youden index on ROC curve).

TABLE 3 Marker levels and diagnostic accuracy in sera from patients withsepsis (n = 44) taken at the time blood was taken for culture, i.e. thetime of symptom onset vs healthy controls (n = 102) sensitivity, 25% 75%specificity Marker group min percentile median percentile max p AUROC(cut-off) CRP control 0 0 0 3 29 <0.0001 .988 95%, 98% mg/L sepsis 3 60104 200 547 (17.5 mg/L) PCT control 0 0 0 0 2 <0.0001 .801 69%, 81% μg/Lsepsis 0 0 2 6.5 80 (0.5 ng/L) sICAM-1 μg/L control 0 129.5 174.5 215.5299 <0.0001 .922 73%, 96% sepsis 146 253.5 408 581 1059 (284 μg/L) IL6control 0 0 3 21 982 <0.0001 .928 98%, 78% ng/L sepsis 0 113 395 12001664 (28.5 ng/L) sPLA2g2a control 0 8 14 22 80 <0.0001 .994 96%, 99%μg/L sepsis 37 63 145 523.5 899 (54.5 μg/L) A1AT control 0 782 1360 21525831 <0.0001 .768 76%, 70% μg/L sepsis 0 1764 2788 4446 10048 (1883mg/L) TNFα control 0 0 0 27 2857 <0.0001 .692 60%, 79% ng/L sepsis 0 064 263 2014 (49 ng/L) CCL23 control 0 75 294 491 2969 <0.0001 .911 89%,81% ng/L Sepsis 77 978 1833 3422 6271 (599 ng/L) MMP8 control 0 6.25 1118.75 49 0.0011 .686 50%, 95% μg/L sepsis 0 8.5 31 40 45 (27.5 μg/L) p =probability, Mann-Whitney U test. AUROC = area under the receiveroperator curve (sensitivity vs 1-specificity). Sensitivity andspecificity determined at the optimum cut-off (maximum Youden index onROC curve).

TABLE 4 Sensitivity and specificity of CRP used alone or in combinationwith other markers in serum samples taken following patient consent andconfirmation of sepsis by a positive blood culture and at the time ofsymptom onset. Marker levels at time Marker levels at time bloodcultures were positive of symptom onset (n = 98 sepsis, (n = 44 sepsis,102 controls) 102 controls) Marker Sensiti- Specifi- Sensiti- Specifi-combinations vity % city % vity % city % CRP alone 94 97 91 99 CRP + PCT95 97 95 99 CRP + sICAM-1 97 98 93 99 CRP + IL6 94 97 93 98 CRP +sPLA2g2a 96 97 98 99 CRP + A1AT 96 97 91 99 CRP + TNF 94 97 91 99 CRP +CCL23 94 97 93 98 CRP + MMP8 94 97 91 99

DISCUSSION

When markers were measured at the time following patient consent andconfirmation of sepsis by a positive blood culture, the accuracy of CRPfor sepsis diagnosis was superior to that of the other markersinvestigated, including PCT. sPLA2g2a was as sensitive as CRP, but itsspecificity was lower. When levels were measured earlier, at the time ofonset of symptoms/admittance of patient to hospital, sPLA2g2a displayeddiagnostic accuracy equivalent to that of CRP. Using both logisticregression and CART, we showed that an increase in the diagnosticaccuracy of CRP could be achieved by combining measurement of CRP withsPLA2g2a. When measured at the time of onset of symptoms/admittance ofpatient to hospital, combination of PLA2 and CRP levels in a logisticregression model gave 100% sensitivity and 100% specificity. ApplyingCART analysis to the combination we generated a diagnostic algorithminvolving the application of CRP at a cut-off of 16.5 mg/L followed bysPLA2g2a at a cut-off of 57.6 pg/L. This gave an accuracy of 100%sensitivity and 97% specificity. If these two markers were measured atthe time blood is taken for culture, their interpretation, either by thelogistic regression model or the diagnostic algorithm, could providesupport for patient management by predicting the blood culture result aseither positive or negative. Most importantly, prediction of a negativeblood culture result might support a decision to withhold antibiotictreatment and thereby avoid unnecessary therapy reducing the risk ofemerging multi antimicrobial resistant microorganisms. Other markersidentified for potential combination with CRP are PCT and sICAM-1, bothof which improved the sensitivity of CRP without compromising itsselectivity in the early samples. For serum samples taken followingpatient consent and confirmation of sepsis by a positive blood culture,sICAM-1 gave a greater improvement in the accuracy of CRP than eithersPLA2g2a or PCT when used in combination with CRP. If a singleadditional marker were to be chosen for combination with CRP, sICAM-1would be recommended for application to samples taken over the timecourse of sepsis before confirmation by positive blood culture. Inpractice, many blood cultures taken from patients with sepsis arenegative due to prior use of antibiotics or inadequate blood volumesampling. In such cases, positive prediction of infection from a markercombination would also support initiation or continuation of antibiotictherapy. Similarly, the use of such combinations of markers may identifywhen positive blood cultures represent contamination rather than truesepsis. This study points the way to those markers that have greatestpotential for combination with CRP. Clearly, the combination ofsPLA2g2a, sICAM-1 or PCT as complementary markers with CRP must berigorously tested in multicentre studies involving other patient groups,including sepsis of fungal aetiology and non-infectious conditionscausing elevated inflammatory and vascular markers. Assays for sPLA2g2aand sICAM-1 could easily be adapted for use in a routine clinicallaboratory.

REFERENCES

-   1. Pierrakos C, Vincent J-L. Sepsis biomarkers: a review. Crit Care    2010; 14: R15.-   2. Tsalik E L, Jaggers L B, Glickman S W, et al. Discriminatory    value of inflammatory biomarkers for suspected sepsis. J Emerg Med    2012; 43: 97-106.-   3. Gaini S, Koldjaer O G, Pedersen C, Pedersen S S (2006).    Procalcitonin, lipopolysaccharide-binding protein, interleukin-6 and    C-reactive protein in community-acquired infections and sepsis: a    prospective study. Crit Care 2006; 10: R53.-   4. Xing K, Murthy S, Liles W C, Singh J M. Clinical utility of    biomarkers of endothelial activation in sepsis-a systematic review.    Critical Care 2012; 16: R7.-   5. Uusitalo-Seppala R, Koskinen P, Leino A, Peuravuori H, Vahlberg    T, Rintala E M.

Early detection of severe sepsis in the emergency room: diagnostic valueof plasma C-reactive protein, procalcitonin, and interleukin-6. Scand JInfect Dis 2011; 43: 883-90.

-   6. Mera S, Tatulescu D, Cismaru C, et al. (2011). Multiplex cytokine    profiling in patients with sepsis. Acta Path Microbiol Immunol Scand    2011; 119: 155-63.-   7. Ginde A A, Blatchford P J, Trzeciak S, et al. (2014). Age-related    differences in biomarkers of acute inflammation during    hospitalization for sepsis. Shock 2014; 42: 99-107.-   8. Kung C T, Hsiao S Y, Su C M, et al. Serum adhesion molecules as    predictors of bacteremia in adult severe sepsis patients at the    emergency department. Clinica Chimica Acta. 2013; 421: 116-20.-   9. Yazdan-Ashoori P, Liaw P, Toltl L, et al. Elevated plasma matrix    metalloproteinases and their tissue inhibitors in patients with    severe sepsis. J Crit Care 2011; 26:556-65.-   10. Rintala E M, Aittoniemi J, Laine S, Nevalainen T J,    Nikoskelainen J. Early identification of bacteremia by biochemical    markers of systemic inflammation. Scand J Clin Lab Invest 2001; 61:    523-30.-   11. Bossink A W, Groeneveld A B, Thijs L G. Prediction of microbial    infection and mortality in medical patients with fever: plasma    procalcitonin, neutrophilic elastase-alpha1-antitrypsin, and    lactoferrin compared with clinical variables. Clinical Infectious    Diseases. 1999; 29: 398-407.-   12. Bone R C, Balk R A, Cerra F B, et al. Definitions for sepsis and    organ failure and guidelines for the use of innovative therapies in    sepsis. The ACCP/SCCM Consensus Conference Committee. American    College of Chest Physicians/Society of Critical Care Medicine. 1992.    Chest 2009; 136(5suppl): e28.

Example 2—UHB Study and Results

Clinical samples made available from a clinical study performed byUniversity Hospital Birmingham (UHB) were tested. They were categorisedaccording to the time of sample:

A=admission/onset of symptoms

B=time blood culture (BC) taken *values in bold represent (Number of A/Bsamples=44)

C=time BC positive=32 samples

D=time of consent (large volume)=88 samples

E=last sample prior to discharge=18 samples

Controls=102 samples

They were tested using the following assays:

Marker Assay Type Format Supplier CRP ELISA Sandwich R&D Systems CRPLateral flow Sandwich Mologic sICAM1 ELISA Sandwich R&D Systems sICAM1Lateral flow Sandwich Mologic CRP/sICAM1 Duplex Lateral flow SandwichMologic IL-6 ELISA Sandwich R&D Systems IL-6 Lateral flow SandwichMologic PLA2 ELISA Sandwich Mologic PLA2 Lateral flow Sandwich MologicIL-6/PLA2 Duplex Lateral flow Sandwich Mologic A1AT ELISA SandwichMologic A1AT Lateral flow Sandwich Mologic TNFα ELISA Sandwich R&DSystems TNFα Lateral flow Sandwich Mologic CCL23 ELISA Sandwich R&DSystems Ac-PGPv3 ELISA Competition Mologic MMP activity SubstrateFluorescent Mologic Creatinine Substrate Colourmetric R&D SystemsDesmosine ELISA Competition Mologic MMP8 ELISA Sandwich R&D SystemsProcalcitonin ELISA Sandwich Abcam Procalcitonin ELISA Sandwich Mologic

Patient demographics were as follows:

All sepsis Gram Negative Gram Positive Control All Male Female All MaleFemale All Male Female All Male Female (n = 105) (n = 59) (n = 46) (n =53) (n = 29) (n = 24) (n = 50) (n = 103) (n = 103) (n = 103) (n = 28) (n= 22) Median age 60 64 55.5 64 69 60.5 54 54.5 46.5 63 63 65 Min Age 2028 20 20 20 33 20 28 20 23 29 23 Max Age 97 97 80 88 88 80 97 97 76 8888 86

The nature of the infections is shown in more detail in FIG. 1.

The origins of the infections are summarised in FIG. 2A for all sepsispatients and in FIG. 2B for gram negative infections and FIG. 2C forgram positive infections respectively.

For each assay logistic regression analysis was performed on the Dsamples versus controls. ROC curves for each of the assays performed areshown in FIG. 3. The results are also summarised in the table below.

Area Under the Curve Test Result Variable(s) Area CRPLF .993 CRPduplex.964 PLA2G2AELISA .950 sICAMELISA .935 CRPELISA .900 sICAMLF .897PLA2G2ALF .827 PLA2G2Aduplex .819 ProcalcitoninELISA .791 sICAMduplex.774 IL6ELISA .731 CCL23ELISA .681 A1ATELISA .657 MMP8ELISA .627 A1ATLF.613 MMPsubstrate .609 TNFaLF .546 TNFaELISA .541 AcPGPELISA .530IL6duplex .493 IL6LF .482 desmosineELISA .471 creatinine .354

As can be seen, some markers displayed good performance when used alone.

Applying a logistic regression analysis of D samples against controlsamples, the following markers were selected for use in combination:CRP, sICAM and TNFalpha. The classification table is provided below:

Classification Table^(a) Predicted VAR00001 Percentage Observed ControlSepsis D Correct Step 1 VAR00001 Control 89 2 97.8 Sepsis D 5 77 93.9Overall Percentage 96.0 Step 2 VAR00001 Control 89 2 97.8 Sepsis D 4 7895.1 Overall Percentage 96.5 Step 3 VAR00001 Control 90 1 98.9 Sepsis D4 78 95.1 Overall Percentage 97.1 ^(a)The cut value is .500

As can be seen from the scatter plot in FIG. 4 and the ROC plot in FIG.5, this combination of markers was able to sensitively and specificallydetect sepsis (as compared to control samples).

The logistic regression model was also applied to A samples veruscontrols and the scatter and boxplot results using this model are shownin FIGS. 6A and 6B respectively.

As can be seen from the ROC plot in FIG. 7, this combination of markerswas also able to sensitively and specifically detect sepsis in theadmission/onset of symptoms samples (as compared to control samples).

Example 3—DSTL Study and Results

910 samples were received and tested on 10 assays at Mologic. Thesamples were collected from patients admitted for elective surgery anddaily samples were collected for up to 7 days post-surgery. The patientswere stratified into 3 different groups:

1. Control group (n=70)—those that recovered with no SIRS symptoms

2. SIRS group (n=66)—those that presented with SIRS symptoms within the7 days

3. Sepsis group (n=70)—those that developed sepsis within the 7 days

Some samples were missing where patients refused consent or the researchnurses failed to get good venous access, and as for the sepsis group,focus was on days −1, −2 and −3 pre-sepsis diagnosis.

Differentiation Between SIRS and Sepsis

Samples were grouped according to DSTL defined SIRS diagnosis based onheart rate, respiratory rate, WCC and temperature and other parameters.The first step was to analyse all samples from patients with sepsis(with SIRS) (n=117) and SIRS (n=173) to come up with the bestcombination to discriminate between the two groups. The markersidentified were sICAM-1 (ELISA and LF), CCL23, A1AT, CRP, IL-6 andTNF-α.

Logistic regression analysis was applied to generate a model forstratifying the patients, as shown in the table below:

sICAM ELISA/LF, CCL23, A1AT, CRP, IL-6 and TNFα Predicted VAR00001Percentage Observed SIRS SEPSIS Correct Step 1 VAR00001 SIRS 147 26 85.0SEPSIS 26 91 71.8 Overall Percentage 82.1 a. The cut value is .500

Using the logistic regression model scatter plots and ROC curves werecreated to show comparisons with all groups. Results for SIRS versussepsis are shown in FIG. 8, for SIRS v controls in FIG. 9 and for sepsisversus controls in FIG. 10. As can be seen, the model was very effectivein distinguishing sepsis from SIRS and also sepsis from controls.

A variety of statistical methods was used to test the significance ofany differences between the three groups. The logistic regressionderived predictive algorithm developed in this report to distinguishindividuals with sepsis compared to SIRS or no SIRS symptoms identifiedseven biomarkers, these being CRP, A1AT, IL-6, sICAM-1 (ELISA and LF)and TNFα. With these biomarker combinations 85% sensitivity for SIRS and71.8% for sepsis was achieved with a p value of <0.0001 (Mann-Whitney ttest) and an AUC value of 0.8754. Overall, these results provide a verystrong basis for the construction of meaningful algorithms and stronglysupport the feasibility of accurate patient monitoring/prediction ofsepsis through the assay of selected biomarkers.

Example 4—Rat Study and Results

Rats were housed in a metabolic monitoring cage for acclimatisationpurposes. They were anaesthetised for 30 minutes for a transthoracicheart scan, and vascular lines were inserted. This was done by making anincision in the centre of the neck and inserting one line into the rightjugular vein and one into the left carotid artery. Sepsis animals weregiven an injection of faecal slurry into the peritoneal cavity, butnaïve animals were not. Blood was taken from the animals from theinserted lines.

There were eight rats in the study, four Naïve and four “Sepsis”following time-points: 0, 3, 6, 12 and 24 hours.

The following assays were run:

Marker Assay Type Dilution IL-6 Quantikine 1 in 2 CRP Duoset 1 in 40ksICAM Duoset 1 in 100, 1in 200 PLA myBiosource Neat TIMP1 Duoset 1 in20, 1 in 1000 MMP8 In-house Neat a1AT myBiosource 1 in 50k

These experiments enabled time courses to be analysed, for example todetect early markers of sepsis which may be of value in predictivemethods. Marker time courses are shown for selected markers in FIGS.11A-D.

Marker time course features:

-   -   IL6 and PLA2 peak at 6 h, rapid decline to 24 h    -   TIMP1 peaks at 6 h, slow decline to 24 h    -   sICAM-1 peaks 12 h, slow decline to 24 h    -   CRP peaks >24 h

Example 5—Sepsis Prototype Point of Care Test

The prototype device is shown schematically in FIG. 12 and consists of asample pad to which 80 μL of a diluted or neat serum sample is added, aconjugate pad containing an optimised mixture of gold colloid-conjugatedantibodies for both the test line(s) and control line. The samplecontaining unknown concentrations of analyte bind to the respectiveantibodies and travels up the nitrocellulose membrane towards thecapture lines. The test line consists of a second antibody to the targetanalyte and if present in the sample will form a complex resulting in avisible test line. The control line consists of an antigen to thecontrol line antibody conjugated to gold i.e. BSA-biotin to anti-biotingold, this will tell the user that the test has run successfully. Alllines are quantifiable within 10 minutes with a lateral flow devicereader such as the Cube (Optricon, Germany).

A personalised testing strategy is set out schematically in FIG. 13.

Example 6—sRAGE in Sepsis

Sixteen samples collected from sepsis patients and 16 samples collectedfrom control subjects were analysed to determine levels of solublereceptor for advanced glycation end products (sRAGE). Higher levels ofsRAGE was found in sepsis patients with a median of 1.425 (IQR1.154-2.337) compared to the control subjects with a median of 1.028(IQR 0.7678-1.212). A significant Mann-Whitney test of 0.0062 wasobtained where a value <0.5 is deemed significant. Box plot results areshown in FIG. 14

ELISA Method:

Reagents: Disposable 96-well polystyrene plates were obtained fromCostar (9018 flat bottomed). Human sRAGE was supplied by Novoprotein(Cat No, C423). Capture antibody sheep anti-sRAGE was obtained fromOrygen antibodies, (Cat No. SA056). Detection antibody Rabbit anti-sRAGE(Cat No, RA040, Orygen antibodies) conjugated to alkaline phosphatase(Innova bioscience 702-0005). PNPP solution was obtained from Biopanda(Cat No. PNPP-001). Sample diluent prepared at Mologic consisted of PBS,pH6.9, supplemented with 1% (v/v) Tween 20) 1% BSA. Wash buffer preparedat Mologic consisted of 50 mM tris buffered saline pH8, supplementedwith 0.1% (v/v) Tween 20.

Pilot production process: Microtitre plates were coated overnight with100 μL of sheep anti-sRAGE SA056 (1 μg/mL in PBS) per well. Plates werewashed 3 times with wash buffer between the blocking step and each ofthe following incubation steps. Each microtitre well was blocked with120 μl of sample diluent for 1 h at room temperature, to minimisenon-specific binding.

Basic assay process: sRAGE was diluted in the sample diluent to giveconcentrations between 5 ng/mL and 0.078 ng/mL to generate thedose-response curve. Samples were added neat. 100 μL Standards and/orsamples were added to microtitre wells and incubated for 1 h at roomtemperature with gentle agitation. Alk-phos conjugated a Rabbitanti-sRAGE RA040 was diluted 1 in 6000 in sample diluent and 100 μLsubsequently added to microtitre wells and incubated for 1 hours at roomtemperature with gentle agitation. 100 μL of pNPP solution was added andincubated for a further 20 minutes. The absorbance was measured at 405nm using a BMG omega plate reader.

Example 7—Decision Tree Analysis of Sepsis Markers

Sera from patients suffering from post-surgical sepsis (n=211) andpost-surgical SIRS (n=288) was analysed by decision tree analysis with aCRT growing method. The combination of markers is CRP, IL-6 and sICAM1.

This decision tree, shown in FIG. 29 has four terminal nodes with SIRSdefined as either CRP<97.582 mg/L or as IL-6<133.910 μg/mL whenCRP>97.582 μg/mL and sICAM1>872.650 ng/mL. Sepsis is defined assICAM1<872.650 ng/mL when CRP is >97.582 or IL-6 >133.910 μg/mL whensICAM1>872.650 ng/mL and CRP>97.582 μg/mL. This decision tree accuratelyidentifies 80.2% of SIRS patients and 72.0% of Sepsis patients, as shownin the table below:

Predicted SIRS Sepsis % correct observed SIRS 231 57 80.2 Sepsis 59 15272.0

Example 8—Diagnostic Performance Using Sofa Scores to Define Sepsis

This study was designed to recruit patients who had undergone electivemajor surgery;

these individuals are at risk of developing post-surgical infections andsepsis.

One serum sample was taken pre-surgery as well as 7 days followingsurgery. The day of onset of SIRS symptoms is designated day 0,preceding days termed day −1, day −2 etc. and days post symptoms of SIRStermed day 1, day 2 etc.

3 cohorts were recruited to the study:

-   -   i) Individuals that developed 2 or more SIRS symptoms+confirmed        or suspected infection    -   ii) Individuals that developed 2 or more SIRS symptoms with no        evidence of infection    -   iii) Individuals that did not develop any SIRS symptoms

Our analysis here is limited to only include groups (i) an (ii) andlimited to the first day of SIRS symptoms.

The markers panel that were tested on these samples:

-   -   CRP, acute phase response    -   IL6 and TNFα, inflammatory cytokines    -   CCL23 (MIP3), a chemokine    -   sICAM-1, vascular endothelial activation*    -   secreted type IIA phospholipase A2 (sPLA2g2a), pro-inflammatory        enzyme    -   acetylated-PGP and desmosine, products of collagen and elastase        respectively    -   α1-antitrypsin (A1AT), protease inhibitor

*sICAM-1 was measured by ELISA and LF. Both these methods of analysis donot correlate to a high degree, suggesting that they are recognisingdifferent (albeit related) targets. These immunoassays contain differentantibody pairs and it is believed that the LF assay is detectingdifferent forms of ICAM including ICAM-1 and VCAM-1.

The patients were differentiated into 2 groups based on having sepsis ornot having sepsis (day one presentation of symptoms):

-   -   1. Infection+SIRS (Infection+2 SIRS criteria (RR, WBC, HR,        Temp))    -   2. SIRS: (2+SIRS criteria (RR, WBC, HR, Temp))

The groups were further defined according to SOFA scores: those based onhaving SOFA 2-6 were grouped:

-   -   1. Infection+SIRS group: Number of patients n=23    -   2. SIRS group: Number of patients n=25

The median SOFA score for both groups was 4.

SOFA Scores for all Patients:

INFECTION + SOFA SIRS SIRS Scores N = 52 N = 44 0 22 15 1 5 6 2 5 4 3 56 4 6 3 5 4 1 6 2 3 8 0 2 9 1 1 10 0 1 13 1 0 14 0 1 15 1 1

Diagnostic Performance with Logistic Regression (LR) Models

Diagnostic performance was initially measured in relation to distinguishthe infection+SIRS group from the SIRS only group.

A first LR model, LR1, was generated using 10 markers: Desmosine, TNF,IL-6, AcPGP, PLA2g2A, CCL23, A1AT, sICAM1 (ELISA), sICAM1 (LF), CRP. LR1gave a Sensitivity of 90.5% and specificity of 88.0% as shown in thetable below and in FIGS. 30A and 30B.

Classification Table - LR1 Predicted VAR00001 Infection + PercentageObserved SIRS SIRS Correct Step 1 VAR00001 SIRS 22 3 88.0 Infection + 219 90.5 SIRS Overall Percentage 89.1

A second model, LR2, was generated using a backwards conditionalLogistic regression function. Five markers were selected: CCL23, A1AT,CRP, sICAMLF and sICAM ELISA. LR2 gave a sensitivity of 85.7% andspecificity of 88.0% as shown in the table below and in FIGS. 31A and31B.

Classification Table - LR2 Predicted VAR00001 Infection + PercentageObserved SIRS SIRS Correct Step 5 VAR00001 SIRS 22 3 88.0 Infection + 318 85.7 SIRS Overall Percentage 87.0

LR2 was also shown to reliably detect SIRS+infection across allpatients, irrespective of SOFA score in sensitive and specific fashion.Results are presented in FIGS. 32A and 32B.

Diagnosing Severity

Diagnostic performance was further measured in relation todistinguishing the infection group with SOFA scores of at least 2 fromthe infection group with SOFA score less than 2.

When tested, LR2 was not able to differentiate SOFA scores of at least 2from SOFA scores less than 2 in either group (data not shown).Accordingly, a third model, LR3, was generated. Seven markers wereselected: CCL23, A1AT, sICAM, desmosine, TNF alpha, IL-6 and PLA2g2A.LR3 was shown to reliably distinguish high SOFA score from low SOFAscore in the infected group to indicate severity (sepsis). Results arepresented in FIGS. 33A and 33B.

Example 9—Validation Study

The validation study was a prospective, observational cohort study ofcritically ill adult patients admitted to the ICU. Following studyapproval from an ethics committee, all patients were screened on a dailybasis to assess those meeting the following inclusion and exclusioncriteria:

Inclusion Criteria

-   -   Multi-organ failure (at least 2 organ systems involved)    -   Initial SOFA score >3    -   Predicted length of ICU stay >3 days

Following consent, patients were enrolled into the study and data wererecorded on a daily basis for the first week and weekly thereafter.Blood sampling was undertaken on the day of admission (Day 0) and,subsequently, on Days 1, 2, 3, 5, 7 and weekly thereafter.

Patient Recruitment

A total of 556 patients were screened for enrolment. Of 177 eligible forinclusion, 51 consented to taking part in the study. Of these, 24patients with either faecal peritonitis or community acquired pneumoniahad samples analysed by Mologic.

Results

As shown in FIG. 34, the LR2 algorithm was able to positively identifythe infected patients in the validation set (based on day 0 samples).

It was also shown that the LR2 algorithm could also be used todiscriminate survivors from non-survivors, see FIG. 35.

The present invention is not to be limited in scope by the specificembodiments described herein. Indeed, various modifications of theinvention in addition to those described herein will become apparent tothose skilled in the art from the foregoing description and accompanyingfigures. Such modifications are intended to fall within the scope of theappended claims. Moreover, all aspects and embodiments of the inventiondescribed herein are considered to be broadly applicable and combinablewith any and all other consistent embodiments, including those takenfrom other aspects of the invention (including in isolation) asappropriate. Various publications are cited herein, the disclosures ofwhich are incorporated by reference in their entireties.

1.-49. (canceled)
 50. A method for predicting sepsis or diagnosingsystemic inflammatory response syndrome (SIRS) and/or sepsis in asubject, the method comprising determining levels of at least threemarkers selected from CCL23, A1AT, CRP, sICAM, PLA2, IL-6,procalcitonin, MMP8, TNFalpha, AcPGP, enzymatic MMP activity, TIMP1,sRAGE and desmosine in a sample taken from the subject, wherein thecombined levels of the at least three markers are used to predict ordiagnose SIRS and/or sepsis.
 51. The method of claim 50 performed on asubject with SIRS and which is used to identify an infection in thesubject.
 52. The method of claim 50 wherein: a) the markers are selectedfrom one or more, up to all, of desmosine, TNF, IL-6, AcPGP, PLA2g2A,CCL23, A1AT, sICAM (optionally measured by ELISA), sICAM/VCAM-1(optionally measured by lateral flow) and CRP; b) the markers areselected from one or more, up to all, of CCL23, A1AT, sICAM (optionallymeasured by ELISA), sICAM/VCAM-1 (optionally measured by lateral flow)and CRP; c) at least one of the markers is selected from CRP, PLA2 andsICAM; d) the markers comprise CRP, sICAM and TNFalpha or CRP, sICAM andIL-6; or e) the method comprises determining levels of at least fourmarkers, optionally wherein the markers comprise PLA2, IL-6, CRP andTNFalpha.
 53. A method for monitoring a subject at risk of developingsepsis, the method comprising determining levels of at least threemarkers in samples taken from the subject at multiple time points,wherein the monitored levels of the at least three markers are used topredict or diagnose SIRS and/or sepsis.
 54. The method of claim 53wherein the subject is a hospitalised patient and/or animmunocompromised patient.
 55. The method of claim 53 wherein thesubject has been subjected to a surgical procedure and the multiple timepoints include a first sample taken from the subject prior to thesurgery to provide baseline levels of the markers and at least onefurther sample taken from the subject following surgery, wherein themonitored levels of the at least three markers are used to predict ordiagnose SIRS and/or sepsis following surgery.
 56. The method of claim50 wherein: a) the method discriminates SIRS from sepsis; b) the methodprovides a prediction of impending sepsis; c) the markers are selectedfrom one or more, up to all, of IL-6, TIMP1, sICAM-1 and PLA2; d) aprediction of impending sepsis results in treatment of the infection; ore) the subject is not treated (e.g. with an antibiotic) unless and untilimpending sepsis is predicted or sepsis is diagnosed.
 57. The method ofclaim 53 wherein: a) the at least three markers are selected from CCL23,A1AT, CRP, sICAM, PLA2, IL-6, procalcitonin, MMP8, TNFalpha, AcPGP,enzymatic MMP activity, TIMP1, sRAGE and desmosine; or b) the method isperformed on a subject with SIRS and which is used to identify aninfection in the subject.
 58. The method of claim 57 wherein: a) themarkers are selected from one or more, up to all, of desmosine, TNF,IL-6, AcPGP, PLA2g2A, CCL23, A1AT, sICAM (optionally measured by ELISA),sICAM/VCAM-1 (optionally measured by lateral flow) and CRP; b) themarkers are selected from one or more, up to all, of CCL23, A1AT, sICAM(optionally measured by ELISA), sICAM/VCAM-1 (optionally measured bylateral flow) and CRP; or c) at least one of the markers is selectedfrom CRP, PLA2 and sICAM.
 59. The method of claim 53 wherein: a) atleast 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14 or more samples aretaken from the subject at different times and the levels of the at leastthree markers is determined; b) the samples are taken every 6 to 24hours, such as daily, or every 3, 4, 5, 6, 7 or 14 days; or c) themethod comprises determining levels of at least four markers.
 60. Themethod of claim 50 wherein: a) the method comprises determining levelsof at least five or six markers, optionally wherein the markers comprisesICAM, CCL23, A1AT, CRP, IL-6 and TNFalpha; or b) the markers comprisesICAM alone (optionally when measured by an ELISA) and sICAM/VCAM-1(optionally sICAM when measured by a lateral flow assay).
 61. A methodof selecting a subject for treatment with an antibiotic comprisingperforming the method of claim 50 and selecting the subject fortreatment where sepsis is predicted or diagnosed; optionally furthercomprising administering an antibiotic to the subject suffering fromsepsis.
 62. A method of treating sepsis comprising administering anantibiotic to the subject suffering from sepsis, wherein the subjectdisplays, in a sample, an altered level of at least three markersselected from CCL23, A1AT, CRP, sICAM, PLA2, IL-6, procalcitonin, MMP8,TNFalpha, AcPGP, enzymatic MMP activity, TIMP1, sRAGE and desmosine. 63.The method of claim 61, wherein the antibiotic is selected from anaminoglycoside, a cephalosporin, a glycopeptide, a penicillin, aquinolone, aztreonam, clindamycin, imipenem-cilastin, linezolid,metronidazole, rifampin and an antifungal.
 64. The method of claim 50,wherein the sample is a whole blood, plasma or serum sample.
 65. Asystem or test kit for predicting or diagnosing systemic inflammatoryresponse syndrome (SIRS) and/or sepsis in a subject, comprising: a) Oneor more testing devices for determining levels of at least three markersselected from CCL23, A1AT, CRP, sICAM, PLA2, IL-6, procalcitonin, MMP8,TNFalpha, AcPGP, enzymatic MMP activity, TIMP1, sRAGE and desmosine in asample b) A processor; and c) A storage medium comprising a computerapplication that, when executed by the processor, is configured to: i)Access and/or calculate the determined levels of each marker in thesample on the one or more testing devices ii) Calculate a test scorefrom the levels of the markers in the sample that predicts or diagnosesSIRS and/or sepsis; and iii) Output from the processor the predicted ordiagnostic result for the subject.
 66. The system or test kit of claim65, wherein a) calculating a test score from the levels of the markersin the sample includes a comparison of the levels with those taken atone or more earlier time points, to thereby predict or diagnose SIRSand/or sepsis; or b) the one or more testing devices determines levelsof at least three markers selected from CCL23, A1AT, CRP, sICAM, PLA2,IL-6, procalcitonin, MMP8, TNFalpha, AcPGP, enzymatic MMP activity,TIMP1, sRAGE and desmosine in a sample at multiple time points includinga first sample taken from the subject prior to the surgery to providebaseline levels of the markers and at least one further sample takenfrom the subject following surgery.
 67. A testing device, testing kit ortesting composition of matter comprising: a) A sample receiving zone towhich a sample from a subject is added; b) A conjugate zone comprisingat least three labelled binding reagents, each of which specificallybinds to one of the at least three markers selected from CCL23, A1AT,CRP, sICAM, PLA2, IL-6, procalcitonin, MMP8, TNFalpha, AcPGP, enzymaticMMP activity, TIMP1, sRAGE and desmosine; and c) A solid supportdefining a liquid flow path for the sample and comprising correspondingtest lines for each of the at least three markers, each test linecomprising an immobilised further binding reagent that also specificallybinds to one of the at least three markers thereby immobilising themarker at the test line to produce a signal via the labelled bindingreagent also specifically bound to the marker.
 68. The testing device,testing kit or testing composition of matter of claim 67 furthercomprising: a) at least one labelled control binding reagent that bindsto a binding partner immobilised at a control line downstream of thetest lines for the at least three markers and thus confirms that thetest has completed successfully; or b) an absorbent material downstreamof the test (and control, where present) lines to absorb excess sample.69. The testing device, testing kit or testing composition of matter ofclaim 67 wherein: a) the sample receiving zone is proportioned toreceive between 10 and 100 μl of serum, such as around 80 μl of serum;b) the solid support comprises a chromatographic medium; c) the solidsupport comprises a capillary flow device; or d) the testing device,testing kit or testing composition is a test strip;
 70. The testingdevice, testing kit or testing composition of matter of claim 67 furthercomprising a reader to quantify levels of the markers at the respectivetest lines.
 71. The testing device, testing kit or testing compositionof matter of claim 70 wherein the reader further comprises a processorand: a) A storage medium comprising a computer application that, whenexecuted by the processor, is configured to: i) Access and/or calculatethe determined levels of each marker in the sample on the one or moretesting devices ii) Calculate a test score from the levels of themarkers in the sample that predicts or diagnoses SIRS and/or sepsis; andiii) Output from the processor the predicted or diagnostic result forthe subject; or b) A storage medium comprising a computer applicationthat, when executed by the processor, is configured to: i) Access and/orcalculate the determined levels of each marker in the sample on the oneor more testing devices ii) Calculate a test score from the levels ofthe markers in the sample by comparing the levels with those taken atone or more earlier time points to thereby predict or diagnose SIRSand/or sepsis; and iii) Output from the processor the predicted ordiagnostic result for the subject.
 72. The system or test kit of claim65 wherein the testing device is a testing device comprising: a) Asample receiving zone to which a sample from a subject is added; b) Aconjugate zone comprising at least three labelled binding reagents, eachof which specifically binds to one of the at least three markersselected from CCL23, A1AT, CRP, sICAM, PLA2, IL-6, procalcitonin, MMP8,TNFalpha, AcPGP, enzymatic MMP activity, TIMP1, sRAGE and desmosine; andc) A solid support defining a liquid flow path for the sample andcomprising corresponding test lines for each of the at least threemarkers, each test line comprising an immobilised further bindingreagent that also specifically binds to one of the at least threemarkers thereby immobilising the marker at the test line to produce asignal via the labelled binding reagent also specifically bound to themarker.